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ORCIDMykel J. Kochenderfer
Mykel John Kochenderfer
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- affiliation: Stanford University
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2020 – today
- 2024
[j49]Erdem Biyik
, Nicolas Huynh, Mykel J. Kochenderfer, Dorsa Sadigh:
Active preference-based Gaussian process regression for reward learning and optimization. Int. J. Robotics Res. 43(5): 665-684 (2024)- [j48]Robert J. Moss, Mykel J. Kochenderfer, Maxime Gariel, Arthur Dubois:
Bayesian Safety Validation for Failure Probability Estimation of Black-Box Systems. J. Aerosp. Inf. Syst. 21(7): 533-546 (2024) - [j47]Victoria Magdalena Dax, Jiachen Li, Enna Sachdeva, Nakul Agarwal, Mykel J. Kochenderfer:
Disentangled Neural Relational Inference for Interpretable Motion Prediction. IEEE Robotics Autom. Lett. 9(2): 1452-1459 (2024) - [j46]Alexandros E. Tzikas, Jinkyoo Park, Mykel J. Kochenderfer, Ross E. Allen:
Distributed Online Planning for Min-Max Problems in Networked Markov Games. IEEE Robotics Autom. Lett. 9(7): 6656-6663 (2024) - [j45]Marija Popovic, Joshua Ott, Julius Rückin, Mykel J. Kochenderfer:
Learning-based methods for adaptive informative path planning. Robotics Auton. Syst. 179: 104727 (2024) - [j44]Joshua Ott, Mykel J. Kochenderfer, Stephen P. Boyd:
Approximate sequential optimization for informative path planning. Robotics Auton. Syst. 182: 104814 (2024) - [j43]Jiachen Li, David Isele, Kanghoon Lee, Jinkyoo Park, Kikuo Fujimura, Mykel J. Kochenderfer:
Interactive Autonomous Navigation With Internal State Inference and Interactivity Estimation. IEEE Trans. Robotics 40: 2932-2949 (2024) - [c175]Isaac R. Ward, Dylan M. Asmar, Mansur Arief, Jana Krystofova Mike, Mykel J. Kochenderfer:
Optimal Control of Mechanical Ventilators with Learned Respiratory Dynamics. CBMS 2024: 192-198 - [c174]Paula Stocco, Suhas Chundi, Arec L. Jamgochian, Mykel J. Kochenderfer:
Addressing Myopic Constrained POMDP Planning with Recursive Dual Ascent. ICAPS 2024: 565-569 - [c173]Arec L. Jamgochian, Hugo Buurmeijer, Kyle Hollins Wray, Anthony Corso, Mykel J. Kochenderfer:
Constrained Hierarchical Monte Carlo Belief-State Planning. ICRA 2024: 2368-2374 - [c172]Bernard Lange, Jiachen Li, Mykel J. Kochenderfer:
Scene Informer: Anchor-based Occlusion Inference and Trajectory Prediction in Partially Observable Environments. ICRA 2024: 14138-14145 - [c171]Robert J. Moss, Arec L. Jamgochian, Johannes Fischer, Anthony Corso, Mykel J. Kochenderfer:
ConstrainedZero: Chance-Constrained POMDP Planning Using Learned Probabilistic Failure Surrogates and Adaptive Safety Constraints. IJCAI 2024: 6752-6760 - [c170]Michael H. Lim, Tyler J. Becker, Mykel J. Kochenderfer, Claire J. Tomlin, Zachary Sunberg:
Optimality Guarantees for Particle Belief Approximation of POMDPs (Abstract Reprint). IJCAI 2024: 8481 - [c169]Maneekwan Toyungyernsub, Esen Yel, Jiachen Li, Mykel J. Kochenderfer:
Predicting Future Spatiotemporal Occupancy Grids with Semantics for Autonomous Driving. IV 2024: 2855-2861 - [c168]Enna Sachdeva, Nakul Agarwal, Suhas Chundi, Sean Roelofs, Jiachen Li, Mykel J. Kochenderfer, Chiho Choi, Behzad Dariush:
Rank2Tell: A Multimodal Driving Dataset for Joint Importance Ranking and Reasoning. WACV 2024: 7498-7507 - [i221]Victoria Magdalena Dax, Jiachen Li, Enna Sachdeva, Nakul Agarwal, Mykel J. Kochenderfer:
Disentangled Neural Relational Inference for Interpretable Motion Prediction. CoRR abs/2401.03599 (2024) - [i220]Victoria Magdalena Dax, Jiachen Li, Kevin Leahy, Mykel J. Kochenderfer:
Graph Q-Learning for Combinatorial Optimization. CoRR abs/2401.05610 (2024) - [i219]Ali Baheri, Mykel J. Kochenderfer:
The Synergy Between Optimal Transport Theory and Multi-Agent Reinforcement Learning. CoRR abs/2401.10949 (2024) - [i218]Jiachen Li, Chuanbo Hua, Hengbo Ma, Jinkyoo Park, Victoria Magdalena Dax, Mykel J. Kochenderfer:
Multi-Agent Dynamic Relational Reasoning for Social Robot Navigation. CoRR abs/2401.12275 (2024) - [i217]Alexandros E. Tzikas, Licio Romao, Mert Pilanci, Alessandro Abate, Mykel J. Kochenderfer:
Distributed Markov Chain Monte Carlo Sampling based on the Alternating Direction Method of Multipliers. CoRR abs/2401.15838 (2024) - [i216]Muhammad Fadhil Ginting, David D. Fan, Sung-Kyun Kim, Mykel J. Kochenderfer, Ali-akbar Agha-mohammadi:
Semantic Belief Behavior Graph: Enabling Autonomous Robot Inspection in Unknown Environments. CoRR abs/2401.17191 (2024) - [i215]Joshua Ott, Mykel J. Kochenderfer, Stephen P. Boyd:
Approximate Sequential Optimization for Informative Path Planning. CoRR abs/2402.08841 (2024) - [i214]Harrison Delecki, Marcell Vazquez-Chanlatte, Esen Yel, Kyle Hollins Wray, Tomer Arnon, Stefan J. Witwicki, Mykel J. Kochenderfer:
Entropy-regularized Point-based Value Iteration. CoRR abs/2402.09388 (2024) - [i213]Paula Stocco, Suhas Chundi, Arec L. Jamgochian, Mykel J. Kochenderfer:
Addressing Myopic Constrained POMDP Planning with Recursive Dual Ascent. CoRR abs/2403.17358 (2024) - [i212]Marija Popovic, Joshua Ott, Julius Rückin, Mykel J. Kochenderfer:
Robotic Learning for Adaptive Informative Path Planning. CoRR abs/2404.06940 (2024) - [i211]Joshua Ott, Edward Balaban, Mykel J. Kochenderfer:
Trajectory Optimization for Adaptive Informative Path Planning with Multimodal Sensing. CoRR abs/2404.18374 (2024) - [i210]Robert J. Moss, Arec L. Jamgochian, Johannes Fischer, Anthony Corso, Mykel J. Kochenderfer:
ConstrainedZero: Chance-Constrained POMDP Planning using Learned Probabilistic Failure Surrogates and Adaptive Safety Constraints. CoRR abs/2405.00644 (2024) - [i209]Muhammad Fadhil Ginting, Sung-Kyun Kim, David D. Fan, Matteo Palieri, Mykel J. Kochenderfer, Ali-Akbar Agha-Mohammadi:
SEEK: Semantic Reasoning for Object Goal Navigation in Real World Inspection Tasks. CoRR abs/2405.09822 (2024) - [i208]Alexandros E. Tzikas, Jinkyoo Park, Mykel J. Kochenderfer, Ross E. Allen:
Distributed Online Planning for Min-Max Problems in Networked Markov Games. CoRR abs/2405.19570 (2024) - [i207]Harrison Delecki, Marc R. Schlichting, Mansur Arief, Anthony Corso, Marcell Vazquez-Chanlatte, Mykel J. Kochenderfer:
Diffusion-Based Failure Sampling for Cyber-Physical Systems. CoRR abs/2406.14761 (2024) - [i206]Mahdi Al-Husseini, Kyle Hollins Wray, Mykel J. Kochenderfer:
Hierarchical Framework for Optimizing Wildfire Surveillance and Suppression using Human-Autonomous Teaming. CoRR abs/2406.17189 (2024) - [i205]Amelia F. Hardy, Houjun Liu, Bernard Lange, Mykel J. Kochenderfer:
ASTPrompter: Weakly Supervised Automated Language Model Red-Teaming to Identify Likely Toxic Prompts. CoRR abs/2407.09447 (2024) - [i204]Anka Reuel, Ben Bucknall, Stephen Casper, Tim Fist, Lisa Soder, Onni Aarne, Lewis Hammond, Lujain Ibrahim, Alan Chan, Peter Wills, Markus Anderljung, Ben Garfinkel, Lennart Heim, Andrew Trask, Gabriel Mukobi, Rylan Schaeffer, Mauricio Baker, Sara Hooker, Irene Solaiman, Alexandra Sasha Luccioni, Nitarshan Rajkumar, Nicolas Moës, Jeffrey Ladish, Neel Guha, Jessica Newman, Yoshua Bengio, Tobin South, Alex Pentland, Sanmi Koyejo, Mykel J. Kochenderfer, Robert Trager:
Open Problems in Technical AI Governance. CoRR abs/2407.14981 (2024) - [i203]Mansur Arief, Mike Timmerman, Jiachen Li, David Isele, Mykel J. Kochenderfer:
Importance Sampling-Guided Meta-Training for Intelligent Agents in Highly Interactive Environments. CoRR abs/2407.15839 (2024) - [i202]Romeo Valentin, Sydney M. Katz, Joonghyun Lee, Don Walker, Matthew Sorgenfrei, Mykel J. Kochenderfer:
Probabilistic Parameter Estimators and Calibration Metrics for Pose Estimation from Image Features. CoRR abs/2407.16223 (2024) - [i201]Bernard Lange, Masha Itkina, Jiachen Li, Mykel J. Kochenderfer:
Self-supervised Multi-future Occupancy Forecasting for Autonomous Driving. CoRR abs/2407.21126 (2024) - [i200]Mahdi Al-Husseini, Kyle Hollins Wray, Mykel J. Kochenderfer:
Watercraft as Overwater Ambulance Exchange Points to Enhance Aeromedical Evacuation. CoRR abs/2408.13847 (2024) - [i199]Zahra Shahrooei, Mykel J. Kochenderfer, Ali Baheri:
Optimizing Falsification for Learning-Based Control Systems: A Multi-Fidelity Bayesian Approach. CoRR abs/2409.08097 (2024) - [i198]Joshua Ott, Mykel J. Kochenderfer, Stephen P. Boyd:
Informative Input Design for Dynamic Mode Decomposition. CoRR abs/2409.13088 (2024) - 2023
- [j42]Alexandros E. Tzikas, Derek Knowles, Grace Xingxin Gao, Mykel J. Kochenderfer:
Multirobot Navigation Using Partially Observable Markov Decision Processes with Belief-Based Rewards. J. Aerosp. Inf. Syst. 20(8): 437-446 (2023) - [j41]Michael H. Lim, Tyler J. Becker, Mykel J. Kochenderfer, Claire J. Tomlin, Zachary N. Sunberg:
Optimality Guarantees for Particle Belief Approximation of POMDPs. J. Artif. Intell. Res. 77: 1591-1636 (2023) - [j40]Ransalu Senanayake, Daniel J. Fremont, Mykel J. Kochenderfer, Alessio R. Lomuscio, Dragos D. Margineantu, Cheng Soon Ong:
Guest Editorial: Special issue on robust machine learning. Mach. Learn. 112(8): 2787-2789 (2023) - [j39]Sydney M. Katz, Kyle D. Julian, Christopher A. Strong, Mykel J. Kochenderfer:
Generating probabilistic safety guarantees for neural network controllers. Mach. Learn. 112(8): 2903-2931 (2023) - [j38]Christopher A. Strong, Haoze Wu, Aleksandar Zeljic, Kyle D. Julian, Guy Katz, Clark W. Barrett, Mykel J. Kochenderfer:
Global optimization of objective functions represented by ReLU networks. Mach. Learn. 112(10): 3685-3712 (2023) - [j37]Raunak P. Bhattacharyya, Blake Wulfe, Derek J. Phillips, Alex Kuefler, Jeremy Morton, Ransalu Senanayake, Mykel J. Kochenderfer:
Modeling Human Driving Behavior Through Generative Adversarial Imitation Learning. IEEE Trans. Intell. Transp. Syst. 24(3): 2874-2887 (2023) - [c167]Arec L. Jamgochian, Anthony Corso, Mykel J. Kochenderfer:
Online Planning for Constrained POMDPs with Continuous Spaces through Dual Ascent. ICAPS 2023: 198-202 - [c166]Zahra Shahrooei, Mykel J. Kochenderfer, Ali Baheri:
Falsification of Learning-Based Controllers through Multi-Fidelity Bayesian Optimization. ECC 2023: 1-6 - [c165]Harrison Delecki, Liam A. Kruse, Marc R. Schlichting, Mykel J. Kochenderfer:
Deep Normalizing Flows for State Estimation. FUSION 2023: 1-6 - [c164]Arec L. Jamgochian, Etienne Bührle, Johannes Fischer, Mykel J. Kochenderfer:
SHAIL: Safety-Aware Hierarchical Adversarial Imitation Learning for Autonomous Driving in Urban Environments. ICRA 2023: 1530-1536 - [c163]Dylan M. Asmar, Ransalu Senanayake, Shawn Manuel, Mykel J. Kochenderfer:
Model Predictive Optimized Path Integral Strategies. ICRA 2023: 3182-3188 - [c162]Muhammad Fadhil Ginting, Sung-Kyun Kim, Oriana Peltzer, Joshua Ott, Sunggoo Jung, Mykel J. Kochenderfer, Ali-akbar Agha-mohammadi:
Safe and Efficient Navigation in Extreme Environments using Semantic Belief Graphs. ICRA 2023: 5653-5658 - [c161]Joshua Ott, Edward Balaban, Mykel J. Kochenderfer:
Sequential Bayesian Optimization for Adaptive Informative Path Planning with Multimodal Sensing. ICRA 2023: 7894-7901 - [c160]Christopher E. Denniston, Oriana Peltzer, Joshua Ott, Sangwoo Moon, Sung-Kyun Kim, Gaurav S. Sukhatme, Mykel J. Kochenderfer, Mac Schwager, Ali-akbar Agha-mohammadi:
Fast and Scalable Signal Inference for Active Robotic Source Seeking. ICRA 2023: 7909-7915 - [c159]Marc R. Schlichting, Nina V. Boord, Anthony L. Corso, Mykel J. Kochenderfer:
SAVME: Efficient Safety Validation for Autonomous Systems Using Meta-Learning. ITSC 2023: 2118-2124 - [c158]Kanghoon Lee, Jiachen Li, David Isele, Jinkyoo Park, Kikuo Fujimura, Mykel J. Kochenderfer:
Robust Driving Policy Learning with Guided Meta Reinforcement Learning. ITSC 2023: 4114-4120 - [c157]Anil Yildiz, Esen Yel, Anthony L. Corso, Kyle Hollins Wray, Stefan J. Witwicki, Mykel J. Kochenderfer:
Experience Filter: Using Past Experiences on Unseen Tasks or Environments. IV 2023: 1-7 - [c156]Harrison Delecki, Anthony Corso, Mykel J. Kochenderfer:
Model-based Validation as Probabilistic Inference. L4DC 2023: 825-837 - [c155]Elysia Q. Smyers, Sydney M. Katz, Anthony Corso, Mykel J. Kochenderfer:
AVOIDDS: Aircraft Vision-based Intruder Detection Dataset and Simulator. NeurIPS 2023 - [c154]Jiankai Sun, Yiqi Jiang, Jianing Qiu, Parth Nobel, Mykel J. Kochenderfer, Mac Schwager:
Conformal Prediction for Uncertainty-Aware Planning with Diffusion Dynamics Model. NeurIPS 2023 - [i197]Christopher E. Denniston, Oriana Peltzer, Joshua Ott, Sangwoo Moon, Sung-Kyun Kim, Gaurav S. Sukhatme, Mykel J. Kochenderfer, Mac Schwager, Ali-akbar Agha-mohammadi:
Fast and Scalable Signal Inference for Active Robotic Source Seeking. CoRR abs/2301.02362 (2023) - [i196]Amanda Bouman, Joshua Ott, Sung-Kyun Kim, Kenny Chen, Mykel J. Kochenderfer, Brett Thomas Lopez, Ali-akbar Agha-mohammadi, Joel Burdick:
Adaptive Coverage Path Planning for Efficient Exploration of Unknown Environments. CoRR abs/2302.03164 (2023) - [i195]Oriana Peltzer, Dylan M. Asmar, Mac Schwager, Mykel J. Kochenderfer:
Incorporating Human Path Preferences in Robot Navigation with Minimal Interventions. CoRR abs/2303.03530 (2023) - [i194]Soyeon Jung, Mykel J. Kochenderfer:
Inferring Traffic Models in Terminal Airspace from Flight Tracks and Procedures. CoRR abs/2303.09981 (2023) - [i193]Muhammad Fadhil Ginting, Sung-Kyun Kim, Oriana Peltzer, Joshua Ott, Sunggoo Jung, Mykel J. Kochenderfer, Ali-akbar Agha-mohammadi:
Safe and Efficient Navigation in Extreme Environments using Semantic Belief Graphs. CoRR abs/2304.00645 (2023) - [i192]Yizheng Wang, Markus Zechner, Gege Wen, Anthony Louis Corso, John Michael Mern, Mykel J. Kochenderfer, Jef Karel Caers:
Optimizing Carbon Storage Operations for Long-Term Safety. CoRR abs/2304.09352 (2023) - [i191]Robert J. Moss, Mykel J. Kochenderfer, Maxime Gariel, Arthur Dubois:
Bayesian Safety Validation for Black-Box Systems. CoRR abs/2305.02449 (2023) - [i190]Ali Baheri, Mykel J. Kochenderfer:
Joint Falsification and Fidelity Settings Optimization for Validation of Safety-Critical Systems: A Theoretical Analysis. CoRR abs/2305.06111 (2023) - [i189]Harrison Delecki, Anthony Corso, Mykel J. Kochenderfer:
Model-based Validation as Probabilistic Inference. CoRR abs/2305.09930 (2023) - [i188]Anil Yildiz, Esen Yel, Anthony L. Corso, Kyle Hollins Wray, Stefan J. Witwicki, Mykel J. Kochenderfer:
Experience Filter: Using Past Experiences on Unseen Tasks or Environments. CoRR abs/2305.18633 (2023) - [i187]Robert J. Moss, Anthony Corso, Jef Caers, Mykel J. Kochenderfer:
BetaZero: Belief-State Planning for Long-Horizon POMDPs using Learned Approximations. CoRR abs/2306.00249 (2023) - [i186]Elysia Q. Smyers, Sydney M. Katz, Anthony L. Corso, Mykel J. Kochenderfer:
AVOIDDS: Aircraft Vision-based Intruder Detection Dataset and Simulator. CoRR abs/2306.11203 (2023) - [i185]Harrison Delecki, Liam A. Kruse, Marc R. Schlichting, Mykel J. Kochenderfer:
Deep Normalizing Flows for State Estimation. CoRR abs/2306.15605 (2023) - [i184]Sydney M. Katz, Anthony L. Corso, Esen Yel, Mykel J. Kochenderfer:
Efficient Determination of Safety Requirements for Perception Systems. CoRR abs/2307.01371 (2023) - [i183]Kanghoon Lee, Jiachen Li, David Isele, Jinkyoo Park, Kikuo Fujimura, Mykel J. Kochenderfer:
Robust Driving Policy Learning with Guided Meta Reinforcement Learning. CoRR abs/2307.10160 (2023) - [i182]Anthony Corso, David Karamadian, Romeo Valentin, Mary Cooper, Mykel J. Kochenderfer:
A Holistic Assessment of the Reliability of Machine Learning Systems. CoRR abs/2307.10586 (2023) - [i181]Enna Sachdeva, Nakul Agarwal, Suhas Chundi, Sean Roelofs, Jiachen Li, Behzad Dariush, Chiho Choi, Mykel J. Kochenderfer:
Rank2Tell: A Multimodal Driving Dataset for Joint Importance Ranking and Reasoning. CoRR abs/2309.06597 (2023) - [i180]Emiko Soroka, Mykel J. Kochenderfer, Sanjay Lall:
Satisfiability.jl: Satisfiability Modulo Theories in Julia. CoRR abs/2309.08778 (2023) - [i179]Marc R. Schlichting, Nina V. Boord, Anthony L. Corso, Mykel J. Kochenderfer:
SAVME: Efficient Safety Validation for Autonomous Systems Using Meta-Learning. CoRR abs/2309.12474 (2023) - [i178]Bernard Lange, Jiachen Li, Mykel J. Kochenderfer:
Scene Informer: Anchor-based Occlusion Inference and Trajectory Prediction in Partially Observable Environments. CoRR abs/2309.13893 (2023) - [i177]Maneekwan Toyungyernsub, Esen Yel, Jiachen Li, Mykel J. Kochenderfer:
Predicting Future Spatiotemporal Occupancy Grids with Semantics for Autonomous Driving. CoRR abs/2310.01723 (2023) - [i176]Arec L. Jamgochian, Hugo Buurmeijer, Kyle Hollins Wray, Anthony Corso, Mykel J. Kochenderfer:
Constrained Hierarchical Monte Carlo Belief-State Planning. CoRR abs/2310.20054 (2023) - [i175]Kyle Brown, Dylan M. Asmar, Mac Schwager, Mykel J. Kochenderfer:
Large-Scale Multi-Robot Assembly Planning for Autonomous Manufacturing. CoRR abs/2311.00192 (2023) - [i174]Jiachen Li, David Isele, Kanghoon Lee, Jinkyoo Park, Kikuo Fujimura, Mykel J. Kochenderfer:
Interactive Autonomous Navigation with Internal State Inference and Interactivity Estimation. CoRR abs/2311.16091 (2023) - 2022
- [j36]Shushman Choudhury, Jayesh K. Gupta, Mykel J. Kochenderfer, Dorsa Sadigh, Jeannette Bohg:
Dynamic multi-robot task allocation under uncertainty and temporal constraints. Auton. Robots 46(1): 231-247 (2022) - [j35]Guy Katz, Clark W. Barrett, David L. Dill, Kyle Julian, Mykel J. Kochenderfer:
Reluplex: a calculus for reasoning about deep neural networks. Formal Methods Syst. Des. 60(1): 87-116 (2022) - [j34]Sydney M. Katz, Anthony L. Corso, Christopher A. Strong, Mykel J. Kochenderfer:
Verification of Image-Based Neural Network Controllers Using Generative Models. J. Aerosp. Inf. Syst. 19(9): 574-584 (2022) - [j33]Shushman Choudhury, Jayesh K. Gupta, Peter Morales, Mykel J. Kochenderfer:
Scalable Online Planning for Multi-Agent MDPs. J. Artif. Intell. Res. 73: 821-846 (2022) - [j32]Chelsea Sidrane, Amir Maleki, Ahmed Irfan, Mykel J. Kochenderfer:
OVERT: An Algorithm for Safety Verification of Neural Network Control Policies for Nonlinear Systems. J. Mach. Learn. Res. 23: 117:1-117:45 (2022) - [j31]Geoffrey Pettet, Ayan Mukhopadhyay, Mykel J. Kochenderfer, Abhishek Dubey:
Hierarchical Planning for Dynamic Resource Allocation in Smart and Connected Communities. ACM Trans. Cyber Phys. Syst. 6(4): 32:1-32:26 (2022) - [j30]Raunak P. Bhattacharyya, Soyeon Jung, Liam A. Kruse, Ransalu Senanayake, Mykel J. Kochenderfer:
A Hybrid Rule-Based and Data-Driven Approach to Driver Modeling Through Particle Filtering. IEEE Trans. Intell. Transp. Syst. 23(8): 13055-13068 (2022) - [j29]Zachary Sunberg, Mykel J. Kochenderfer:
Improving Automated Driving Through POMDP Planning With Human Internal States. IEEE Trans. Intell. Transp. Syst. 23(11): 20073-20083 (2022) - [c153]Soyeon Jung, Ransalu Senanayake, Mykel J. Kochenderfer:
A Gray Box Model for Characterizing Driver Behavior. SafeAI@AAAI 2022 - [c152]Xiaobai Ma, David Isele, Jayesh K. Gupta, Kikuo Fujimura, Mykel J. Kochenderfer:
Recursive Reasoning Graph for Multi-Agent Reinforcement Learning. AAAI 2022: 7664-7671 - [c151]John Mern, Sidhart Krishnan, Anil Yildiz, Kyle Hatch, Mykel J. Kochenderfer:
Interpretable Local Tree Surrogate Policies. SafeAI@AAAI 2022 - [c150]Ann-Katrin Reuel, Mark Koren, Anthony Corso, Mykel J. Kochenderfer:
Using Adaptive Stress Testing to Identify Paths to Ethical Dilemmas in Autonomous Systems. SafeAI@AAAI 2022 - [c149]Shushman Choudhury, Kiril Solovey, Mykel J. Kochenderfer, Marco Pavone:
Coordinated Multi-Agent Pathfinding for Drones and Trucks over Road Networks. AAMAS 2022: 272-280 - [c148]Jennifer She, Jayesh K. Gupta, Mykel J. Kochenderfer:
Agent-Time Attention for Sparse Rewards Multi-Agent Reinforcement Learning. AAMAS 2022: 1723-1725 - [c147]Masha Itkina, Mykel J. Kochenderfer:
Interpretable Self-Aware Neural Networks for Robust Trajectory Prediction. CoRL 2022: 606-617 - [c146]John Mern, Kyle Hatch, Ryan Silva, Cameron Hickert, Tamim Sookoor, Mykel J. Kochenderfer:
Autonomous Attack Mitigation for Industrial Control Systems. DSN Workshops 2022: 28-36 - [c145]Lisa J. Einstein, Robert J. Moss, Mykel J. Kochenderfer:
Prioritizing emergency evacuations under compounding levels of uncertainty. GHTC 2022: 265-272 - [c144]Eric Luxenberg, Stephen P. Boyd, Misha van Beek, Wen Cao, Mykel J. Kochenderfer:
Strategic Asset Allocation with Illiquid Alternatives. ICAIF 2022: 249-256 - [c143]Masha Itkina, Ye-Ji Mun, Katherine Driggs Campbell, Mykel J. Kochenderfer:
Multi-Agent Variational Occlusion Inference Using People as Sensors. ICRA 2022: 4585-4591 - [c142]Sheng Li, Yutai Zhou, Ross E. Allen, Mykel J. Kochenderfer:
Learning Emergent Discrete Message Communication for Cooperative Reinforcement Learning. ICRA 2022: 5511-5517 - [c141]Victoria Magdalena Dax, Mykel J. Kochenderfer, Ransalu Senanayake, Umair Ibrahim:
Infrastructure-Enabled Autonomy: An Attention Mechanism for Occlusion Handling. ICRA 2022: 5939-5945 - [c140]Shushman Choudhury, Jayesh K. Gupta, Mykel J. Kochenderfer:
Scalable Anytime Planning for Multi-Agent MDPs (Extended Abstract). IJCAI 2022: 5279-5283 - [c139]Harrison Delecki, Masha Itkina, Bernard Lange, Ransalu Senanayake, Mykel J. Kochenderfer:
How Do We Fail? Stress Testing Perception in Autonomous Vehicles. IROS 2022: 5139-5146 - [c138]Muhammad Fadhil Ginting, Kyohei Otsu, Mykel J. Kochenderfer, Ali-akbar Agha-mohammadi:
Capability-Aware Task Allocation and Team Formation Analysis for Cooperative Exploration of Complex Environments. IROS 2022: 7145-7152 - [c137]Oriana Peltzer, Amanda Bouman, Sung-Kyun Kim, Ransalu Senanayake, Joshua Ott, Harrison Delecki, Mamoru Sobue, Mykel J. Kochenderfer, Mac Schwager, Joel Burdick, Ali-akbar Agha-mohammadi:
FIG-OP: Exploring Large-Scale Unknown Environments on a Fixed Time Budget. IROS 2022: 8754-8761 - [c136]Kyle Hollins Wray, Stas Tiomkin, Mykel J. Kochenderfer, Pieter Abbeel:
Multi-Objective Policy Gradients with Topological Constraints. IROS 2022: 9034-9039 - [c135]Maneekwan Toyungyernsub, Esen Yel, Jiachen Li, Mykel J. Kochenderfer:
Dynamics-Aware Spatiotemporal Occupancy Prediction in Urban Environments. IROS 2022: 10836-10841 - [c134]Amanda Bouman, Joshua Ott, Sung-Kyun Kim, Kenny Chen, Mykel J. Kochenderfer, Brett Thomas Lopez, Ali-akbar Agha-mohammadi, Joel Burdick:
Adaptive Coverage Path Planning for Efficient Exploration of Unknown Environments. IROS 2022: 11916-11923 - [c133]Liam A. Kruse, Esen Yel, Ransalu Senanayake, Mykel J. Kochenderfer:
Uncertainty-Aware Online Merge Planning with Learned Driver Behavior. ITSC 2022: 1202-1207 - [c132]Samuel Low, Mykel J. Kochenderfer:
Optimal Pointing Sequences in Spacecraft Formation Flying Using Online Planning with Resource Constraints. L4DC 2022: 355-365 - [c131]Christopher A. Strong, Sydney M. Katz, Anthony L. Corso, Mykel J. Kochenderfer:
ZoPE: A Fast Optimizer for ReLU Networks with Low-Dimensional Inputs. NFM 2022: 299-317 - [c130]Dylan M. Asmar, Mykel J. Kochenderfer:
Collaborative Decision Making Using Action Suggestions. NeurIPS 2022 - [c129]Anthony Corso, Sydney M. Katz, Craig Innes, Xin Du, Subramanian Ramamoorthy, Mykel J. Kochenderfer:
Risk-Driven Design of Perception Systems. NeurIPS 2022 - [c128]Fan-Yun Sun, Isaac Kauvar, Ruohan Zhang, Jiachen Li, Mykel J. Kochenderfer, Jiajun Wu, Nick Haber:
Interaction Modeling with Multiplex Attention. NeurIPS 2022 - [e1]Roya Firoozi, Negar Mehr, Esen Yel, Rika Antonova, Jeannette Bohg, Mac Schwager, Mykel J. Kochenderfer:
Learning for Dynamics and Control Conference, L4DC 2022, 23-24 June 2022, Stanford University, Stanford, CA, USA. Proceedings of Machine Learning Research 168, PMLR 2022 [contents] - [i173]Arec L. Jamgochian, Kunal Menda, Mykel J. Kochenderfer:
Multi-Vehicle Control in Roundabouts using Decentralized Game-Theoretic Planning. CoRR abs/2201.02718 (2022) - [i172]Arec L. Jamgochian, Di Wu, Kunal Menda, Soyeon Jung, Mykel J. Kochenderfer:
Conditional Approximate Normalizing Flows for Joint Multi-Step Probabilistic Forecasting with Application to Electricity Demand. CoRR abs/2201.02753 (2022) - [i171]Chelsea Sidrane, Sydney M. Katz, Anthony Corso, Mykel J. Kochenderfer:
Verifying Inverse Model Neural Networks. CoRR abs/2202.02429 (2022) - [i170]Gabriel Maher, Stephen P. Boyd, Mykel John Kochenderfer, Cristian Matache, Alex Ulitsky, Slava Yukhymuk, Leonid Kopman:
A Light-Weight Multi-Objective Asynchronous Hyper-Parameter Optimizer. CoRR abs/2202.07735 (2022) - [i169]Xiaobai Ma, David Isele, Jayesh K. Gupta, Kikuo Fujimura, Mykel J. Kochenderfer:
Recursive Reasoning Graph for Multi-Agent Reinforcement Learning. CoRR abs/2203.02844 (2022) - [i168]Christopher Lazarus, Mykel J. Kochenderfer:
Deep Binary Reinforcement Learning for Scalable Verification. CoRR abs/2203.05704 (2022) - [i167]Oriana Peltzer, Amanda Bouman, Sung-Kyun Kim, Ransalu Senanayake, Joshua Ott, Harrison Delecki, Mamoru Sobue, Mykel J. Kochenderfer, Mac Schwager, Joel Burdick, Ali-akbar Agha-mohammadi:
FIG-OP: Exploring Large-Scale Unknown Environments on a Fixed Time Budget. CoRR abs/2203.06316 (2022) - [i166]Christopher Lazarus, Mykel J. Kochenderfer:
A Mixed Integer Programming Approach for Verifying Properties of Binarized Neural Networks. CoRR abs/2203.07078 (2022) - [i165]Harrison Delecki, Masha Itkina, Bernard Lange, Ransalu Senanayake, Mykel J. Kochenderfer:
How Do We Fail? Stress Testing Perception in Autonomous Vehicles. CoRR abs/2203.14155 (2022) - [i164]Dylan M. Asmar, Ransalu Senanayake, Shawn Manuel, Mykel J. Kochenderfer:
Model Predictive Optimized Path Integral Strategies. CoRR abs/2203.16633 (2022) - [i163]Arec L. Jamgochian, Etienne Bührle, Johannes Fischer, Mykel J. Kochenderfer:
SHAIL: Safety-Aware Hierarchical Adversarial Imitation Learning for Autonomous Driving in Urban Environments. CoRR abs/2204.01922 (2022) - [i162]Sydney M. Katz, Luis E. Alvarez, Michael P. Owen, Samuel Wu, Marc Brittain, Anshuman Das, Mykel J. Kochenderfer:
Collision Risk and Operational Impact of Speed Change Advisories as Aircraft Collision Avoidance Maneuvers. CoRR abs/2204.14250 (2022) - [i161]Anthony L. Corso, Sydney M. Katz, Craig Innes, Xin Du, Subramanian Ramamoorthy, Mykel J. Kochenderfer:
Risk-Driven Design of Perception Systems. CoRR abs/2205.10677 (2022) - [i160]Junyoung Park, Federico Berto, Arec L. Jamgochian, Mykel J. Kochenderfer, Jinkyoo Park:
Meta-SysId: A Meta-Learning Approach for Simultaneous Identification and Prediction. CoRR abs/2206.00694 (2022) - [i159]Bertrand Charpentier, Ransalu Senanayake, Mykel J. Kochenderfer, Stephan Günnemann:
Disentangling Epistemic and Aleatoric Uncertainty in Reinforcement Learning. CoRR abs/2206.01558 (2022) - [i158]Liam A. Kruse, Esen Yel, Ransalu Senanayake, Mykel J. Kochenderfer:
Uncertainty-Aware Online Merge Planning with Learned Driver Behavior. CoRR abs/2207.05228 (2022) - [i157]Eric Luxenberg, Stephen P. Boyd, Mykel J. Kochenderfer, Misha van Beek, Wen Cao, Steven Diamond, Alex Ulitsky, Kunal Menda, Vidy Vairavamurthy:
Strategic Asset Allocation with Illiquid Alternatives. CoRR abs/2207.07767 (2022) - [i156]Jiachen Li, Chuanbo Hua, Jinkyoo Park, Hengbo Ma, Victoria Magdalena Dax, Mykel J. Kochenderfer:
EvolveHypergraph: Group-Aware Dynamic Relational Reasoning for Trajectory Prediction. CoRR abs/2208.05470 (2022) - [i155]Fan-Yun Sun, Isaac Kauvar, Ruohan Zhang, Jiachen Li, Mykel J. Kochenderfer, Jiajun Wu, Nick Haber:
Interaction Modeling with Multiplex Attention. CoRR abs/2208.10660 (2022) - [i154]Joshua Ott, Sung-Kyun Kim, Amanda Bouman, Oriana Peltzer, Mamoru Sobue, Harrison Delecki, Mykel J. Kochenderfer, Joel Burdick, Ali-akbar Agha-mohammadi:
Risk-aware Meta-level Decision Making for Exploration Under Uncertainty. CoRR abs/2209.05580 (2022) - [i153]Kyle Hollins Wray, Stas Tiomkin, Mykel J. Kochenderfer, Pieter Abbeel:
Multi-Objective Policy Gradients with Topological Constraints. CoRR abs/2209.07096 (2022) - [i152]Joshua Ott, Edward Balaban, Mykel J. Kochenderfer:
Sequential Bayesian Optimization for Adaptive Informative Path Planning with Multimodal Sensing. CoRR abs/2209.07660 (2022) - [i151]Dylan M. Asmar, Mykel J. Kochenderfer:
Collaborative Decision Making Using Action Suggestions. CoRR abs/2209.13160 (2022) - [i150]Maneekwan Toyungyernsub, Esen Yel, Jiachen Li, Mykel J. Kochenderfer:
Dynamics-Aware Spatiotemporal Occupancy Prediction in Urban Environments. CoRR abs/2209.13172 (2022) - [i149]Nicholas Rober, Sydney M. Katz, Chelsea Sidrane, Esen Yel, Michael Everett, Mykel J. Kochenderfer, Jonathan P. How:
Backward Reachability Analysis of Neural Feedback Loops: Techniques for Linear and Nonlinear Systems. CoRR abs/2209.14076 (2022) - [i148]Bernard Lange, Masha Itkina, Mykel J. Kochenderfer:
LOPR: Latent Occupancy PRediction using Generative Models. CoRR abs/2210.01249 (2022) - [i147]Michael H. Lim, Tyler J. Becker, Mykel J. Kochenderfer, Claire J. Tomlin, Zachary N. Sunberg:
Generalized Optimality Guarantees for Solving Continuous Observation POMDPs through Particle Belief MDP Approximation. CoRR abs/2210.05015 (2022) - [i146]Lisa J. Einstein, Robert J. Moss, Mykel J. Kochenderfer:
Prioritizing emergency evacuations under compounding levels of uncertainty. CoRR abs/2210.08975 (2022) - [i145]Jennifer She, Jayesh K. Gupta, Mykel J. Kochenderfer:
Agent-Time Attention for Sparse Rewards Multi-Agent Reinforcement Learning. CoRR abs/2210.17540 (2022) - [i144]Masha Itkina, Mykel J. Kochenderfer:
Interpretable Self-Aware Neural Networks for Robust Trajectory Prediction. CoRR abs/2211.08701 (2022) - [i143]Anthony Corso, Kyu-Young Kim, Shubh Gupta, Grace Gao, Mykel J. Kochenderfer:
A Deep Reinforcement Learning Approach to Rare Event Estimation. CoRR abs/2211.12470 (2022) - [i142]Anthony Corso, Yizheng Wang, Markus Zechner, Jef Caers, Mykel J. Kochenderfer:
A POMDP Model for Safe Geological Carbon Sequestration. CoRR abs/2212.00669 (2022) - [i141]Arec L. Jamgochian, Anthony Corso, Mykel J. Kochenderfer:
Online Planning for Constrained POMDPs with Continuous Spaces through Dual Ascent. CoRR abs/2212.12154 (2022) - [i140]Zahra Shahrooei, Mykel J. Kochenderfer, Ali Baheri:
Falsification of Learning-Based Controllers through Multi-Fidelity Bayesian Optimization. CoRR abs/2212.14118 (2022) - 2021
- [j28]Changliu Liu, Tomer Arnon, Christopher Lazarus, Christopher A. Strong, Clark W. Barrett, Mykel J. Kochenderfer:
Algorithms for Verifying Deep Neural Networks. Found. Trends Optim. 4(3-4): 244-404 (2021) - [j27]Shushman Choudhury, Kiril Solovey, Mykel J. Kochenderfer, Marco Pavone:
Efficient Large-Scale Multi-Drone Delivery using Transit Networks. J. Artif. Intell. Res. 70: 757-788 (2021) - [j26]Anthony Corso, Robert J. Moss, Mark Koren, Ritchie Lee, Mykel J. Kochenderfer:
A Survey of Algorithms for Black-Box Safety Validation of Cyber-Physical Systems. J. Artif. Intell. Res. 72: 377-428 (2021) - [j25]Nicholas Moehle, Mykel J. Kochenderfer, Stephen P. Boyd, Andrew Ang:
Tax-Aware Portfolio Construction via Convex Optimization. J. Optim. Theory Appl. 189(2): 364-383 (2021) - [j24]Patrick Slade, Arjun Tambe, Mykel J. Kochenderfer:
Multimodal sensing and intuitive steering assistance improve navigation and mobility for people with impaired vision. Sci. Robotics 6(59) (2021) - [c127]Anthony Corso, Mykel J. Kochenderfer:
Transfer Learning for Efficient Iterative Safety Validation. AAAI 2021: 7125-7132 - [c126]John Mern, Anil Yildiz, Zachary Sunberg, Tapan Mukerji, Mykel J. Kochenderfer:
Bayesian Optimized Monte Carlo Planning. AAAI 2021: 11880-11887 - [c125]John Mern, Anil Yildiz, Lawrence Bush, Tapan Mukerji, Mykel J. Kochenderfer:
Improved POMDP Tree Search Planning with Prioritized Action Branching. AAAI 2021: 11888-11894 - [c124]Shushman Choudhury, Jayesh K. Gupta, Peter Morales, Mykel J. Kochenderfer:
Scalable Anytime Planning for Multi-Agent MDPs. AAMAS 2021: 341-349 - [c123]Sheng Li, Jayesh K. Gupta, Peter Morales, Ross E. Allen, Mykel J. Kochenderfer:
Deep Implicit Coordination Graphs for Multi-agent Reinforcement Learning. AAMAS 2021: 764-772 - [c122]Geoffrey Pettet, Ayan Mukhopadhyay, Mykel J. Kochenderfer, Abhishek Dubey:
Hierarchical planning for resource allocation in emergency response systems. ICCPS 2021: 155-166 - [c121]Liam A. Kruse, Allan L. Reiss, Mykel J. Kochenderfer, Stephanie Balters:
Dyadic Sex Composition and Task Classification Using fNIRS Hyperscanning Data. ICMLA 2021: 582-588 - [c120]Xiaobai Ma, Jiachen Li, Mykel J. Kochenderfer, David Isele, Kikuo Fujimura:
Reinforcement Learning for Autonomous Driving with Latent State Inference and Spatial-Temporal Relationships. ICRA 2021: 6064-6071 - [c119]Maneekwan Toyungyernsub, Masha Itkina, Ransalu Senanayake, Mykel J. Kochenderfer:
Double-Prong ConvLSTM for Spatiotemporal Occupancy Prediction in Dynamic Environments. ICRA 2021: 13931-13937 - [c118]Christopher Lazarus, Mykel J. Kochenderfer:
A Mixed Integer Programming Approach for Verifying Properties of Binarized Neural Networks. AISafety@IJCAI 2021 - [c117]Bernard Lange, Masha Itkina, Mykel J. Kochenderfer:
Attention Augmented ConvLSTM for Environment Prediction. IROS 2021: 1346-1353 - [c116]Ransalu Senanayake, Kyle Beltran Hatch, Jason Zheng, Mykel J. Kochenderfer:
3D Radar Velocity Maps for Uncertain Dynamic Environments. IROS 2021: 4854-4860 - [c115]Mark Koren, Ahmed Nassar, Mykel J. Kochenderfer:
Finding Failures in High-Fidelity Simulation using Adaptive Stress Testing and the Backward Algorithm. IROS 2021: 5944-5949 - [c114]Julia Nitsch, Masha Itkina, Ransalu Senanayake, Juan I. Nieto, Max Schmidt, Roland Siegwart, Mykel J. Kochenderfer, Cesar Cadena:
Out-of-Distribution Detection for Automotive Perception. ITSC 2021: 2938-2943 - [c113]Phil Chen, Masha Itkina, Ransalu Senanayake, Mykel J. Kochenderfer:
Evidential Softmax for Sparse Multimodal Distributions in Deep Generative Models. NeurIPS 2021: 11565-11576 - [c112]Samriddhi Singla, Ayan Mukhopadhyay, Michael Wilbur, Tina Diao, Vinayak Gajjewar, Ahmed Eldawy, Mykel J. Kochenderfer, Ross D. Shachter, Abhishek Dubey:
WildfireDB: An Open-Source Dataset Connecting Wildfire Occurrence with Relevant Determinants. NeurIPS Datasets and Benchmarks 2021 - [d9]Duncan Eddy, Mykel J. Kochenderfer:
Maximum Independent Set Satellite Scheduling World Cities Data Set. Zenodo, 2021
- [d8]Andrew Weinert, Mykel J. Kochenderfer, Matthew W. M. Edwards:
Airspace-Encounter-Models/em-model-manned-bayes: March 2021 - OpenSky Updates. Version v1.3. Zenodo, 2021 [all versions] - [d7]Andrew J. Weinert, Mykel J. Kochenderfer, Matthew W. M. Edwards, Bilal Gill, Randal Guendel, Christine Serres, Ngaire Underhill:
Airspace-Encounter-Models/em-model-manned-bayes: July 2021 - Terminal Model and Improved Performance. Version v1.4. Zenodo, 2021 [all versions] - [d6]Andrew J. Weinert, Mykel J. Kochenderfer, Matthew W. M. Edwards, Bilal Gill, Randal Guendel, Christine Serres, Ngaire Underhill:
Airspace-Encounter-Models/em-model-manned-bayes: October 2021. Version v2.0.0. Zenodo, 2021 [all versions] - [d5]Andrew J. Weinert, Mykel J. Kochenderfer, Matthew W. M. Edwards, Bilal Gill, Randal Guendel, Christine Serres, Ngaire Underhill:
Airspace-Encounter-Models/em-model-manned-bayes: October 2021. Version v2.1.0. Zenodo, 2021 [all versions] - [i139]Shushman Choudhury, Jayesh K. Gupta, Peter Morales, Mykel J. Kochenderfer:
Scalable Anytime Planning for Multi-Agent MDPs. CoRR abs/2101.04788 (2021) - [i138]Sheng Li, Yutai Zhou, Ross E. Allen, Mykel J. Kochenderfer:
Learning Emergent Discrete Message Communication for Cooperative Reinforcement Learning. CoRR abs/2102.12550 (2021) - [i137]Sydney M. Katz, Kyle D. Julian, Christopher A. Strong, Mykel J. Kochenderfer:
Generating Probabilistic Safety Guarantees for Neural Network Controllers. CoRR abs/2103.01203 (2021) - [i136]Sydney M. Katz, Amir Maleki, Erdem Biyik, Mykel J. Kochenderfer:
Preference-based Learning of Reward Function Features. CoRR abs/2103.02727 (2021) - [i135]Kunal Menda, Jayesh K. Gupta, Zachary Manchester, Mykel J. Kochenderfer:
Training Structured Mechanical Models by Minimizing Discrete Euler-Lagrange Residual. CoRR abs/2105.01811 (2021) - [i134]Sydney M. Katz, Anthony L. Corso, Christopher A. Strong, Mykel J. Kochenderfer:
Verification of Image-based Neural Network Controllers Using Generative Models. CoRR abs/2105.07091 (2021) - [i133]John Mern, Mykel J. Kochenderfer:
Measurable Monte Carlo Search Error Bounds. CoRR abs/2106.04715 (2021) - [i132]Christopher A. Strong, Sydney M. Katz, Anthony L. Corso, Mykel J. Kochenderfer:
ZoPE: A Fast Optimizer for ReLU Networks with Low-Dimensional Inputs. CoRR abs/2106.05325 (2021) - [i131]John Mern, Kyle Hatch, Ryan Silva, Jeff Brush, Mykel J. Kochenderfer:
Reinforcement Learning for Industrial Control Network Cyber Security Orchestration. CoRR abs/2106.05332 (2021) - [i130]Geoffrey Pettet, Ayan Mukhopadhyay, Mykel J. Kochenderfer, Abhishek Dubey:
Hierarchical Planning for Dynamic Resource Allocation in Smart and Connected Communities. CoRR abs/2107.01292 (2021) - [i129]Ransalu Senanayake, Kyle Beltran Hatch, Jason Zheng, Mykel J. Kochenderfer:
3D Radar Velocity Maps for Uncertain Dynamic Environments. CoRR abs/2107.11039 (2021) - [i128]Mark Koren, Ahmed Nassar, Mykel J. Kochenderfer:
Finding Failures in High-Fidelity Simulation using Adaptive Stress Testing and the Backward Algorithm. CoRR abs/2107.12940 (2021) - [i127]Chelsea Sidrane, Amir Maleki, Ahmed Irfan, Mykel J. Kochenderfer:
OVERT: An Algorithm for Safety Verification of Neural Network Control Policies for Nonlinear Systems. CoRR abs/2108.01220 (2021) - [i126]Raunak P. Bhattacharyya, Soyeon Jung, Liam Kruse, Ransalu Senanayake, Mykel J. Kochenderfer:
A Hybrid Rule-Based and Data-Driven Approach to Driver Modeling through Particle Filtering. CoRR abs/2108.12820 (2021) - [i125]Masha Itkina, Ye-Ji Mun, Katherine Driggs Campbell, Mykel J. Kochenderfer:
Multi-Agent Variational Occlusion Inference Using People as Sensors. CoRR abs/2109.02173 (2021) - [i124]John Mern, Sidhart Krishnan, Anil Yildiz, Kyle Hatch, Mykel J. Kochenderfer:
Interpretable Local Tree Surrogate Policies. CoRR abs/2109.08180 (2021) - [i123]Shushman Choudhury, Kiril Solovey, Mykel J. Kochenderfer, Marco Pavone:
Coordinated Multi-Agent Pathfinding for Drones and Trucks over Road Networks. CoRR abs/2110.08802 (2021) - [i122]Phil Chen, Masha Itkina, Ransalu Senanayake, Mykel J. Kochenderfer:
Evidential Softmax for Sparse Multimodal Distributions in Deep Generative Models. CoRR abs/2110.14182 (2021) - [i121]John Mern, Kyle Hatch, Ryan Silva, Cameron Hickert, Tamim Sookoor, Mykel J. Kochenderfer:
Autonomous Attack Mitigation for Industrial Control Systems. CoRR abs/2111.02445 (2021) - [i120]Liam A. Kruse, Allan L. Reiss, Mykel J. Kochenderfer, Stephanie Balters:
Dyadic Sex Composition and Task Classification Using fNIRS Hyperscanning Data. CoRR abs/2112.03911 (2021) - 2020
- [j23]Bohan Wu, Jayesh K. Gupta, Mykel J. Kochenderfer:
Model primitives for hierarchical lifelong reinforcement learning. Auton. Agents Multi Agent Syst. 34(1): 28 (2020) - [j22]Patrick Slade, Zachary N. Sunberg, Mykel J. Kochenderfer:
Estimation and control using sampling-based Bayesian reinforcement learning. IET Cyper-Phys. Syst.: Theory & Appl. 5(1): 127-135 (2020) - [j21]Ritchie Lee, Ole J. Mengshoel, Anshu Saksena, Ryan W. Gardner, Daniel Genin, Joshua Silbermann, Michael P. Owen, Mykel J. Kochenderfer:
Adaptive Stress Testing: Finding Likely Failure Events with Reinforcement Learning. J. Artif. Intell. Res. 69: 1165-1201 (2020) - [j20]Carl-Johan Hoel, Katherine Rose Driggs-Campbell, Krister Wolff, Leo Laine, Mykel J. Kochenderfer:
Combining Planning and Deep Reinforcement Learning in Tactical Decision Making for Autonomous Driving. IEEE Trans. Intell. Veh. 5(2): 294-305 (2020) - [c111]Maxime Bouton, Jana Tumova, Mykel J. Kochenderfer:
Point-Based Methods for Model Checking in Partially Observable Markov Decision Processes. AAAI 2020: 10061-10068 - [c110]Tina Diao, Samriddhi Singla, Ayan Mukhopadhyay, Ahmed Eldawy, Ross D. Shachter, Mykel J. Kochenderfer:
Uncertainty Aware Wildfire Management. AI4SG@AAAI Fall Symposium 2020 - [c109]Ayan Mukhopadhyay, Geoffrey Pettet, Mykel J. Kochenderfer, Abhishek Dubey:
Designing Emergency Response Pipelines : Lessons and Challenges. AI4SG@AAAI Fall Symposium 2020 - [c108]Shushman Choudhury, Nate Gruver, Mykel J. Kochenderfer:
Adaptive Informative Path Planning with Multimodal Sensing. ICAPS 2020: 57-65 - [c107]Raunak P. Bhattacharyya, Ransalu Senanayake, Kyle Brown, Mykel J. Kochenderfer:
Online Parameter Estimation for Human Driver Behavior Prediction. ACC 2020: 301-306 - [c106]John Mern, Dorsa Sadigh, Mykel J. Kochenderfer:
Exchangeable Input Representations for Reinforcement Learning. ACC 2020: 3971-3976 - [c105]Geoffrey Pettet, Ayan Mukhopadhyay, Mykel J. Kochenderfer, Yevgeniy Vorobeychik, Abhishek Dubey:
On Algorithmic Decision Procedures in Emergency Response Systems in Smart and Connected Communities. AAMAS 2020: 1046-1054 - [c104]Nate Gruver, Jiaming Song, Mykel J. Kochenderfer, Stefano Ermon:
Multi-agent Adversarial Inverse Reinforcement Learning with Latent Variables. AAMAS 2020: 1855-1857 - [c103]Xiaobai Ma, Jayesh K. Gupta, Mykel J. Kochenderfer:
Normalizing Flow Model for Policy Representation in Continuous Action Multi-agent Systems. AAMAS 2020: 1916-1918 - [c102]Xiaobai Ma, Jayesh K. Gupta, Mykel J. Kochenderfer:
Normalizing Flow Policies for Multi-agent Systems. GameSec 2020: 277-296 - [c101]Kunal Menda, Jean de Becdelièvre, Jayesh K. Gupta, Ilan Kroo, Mykel J. Kochenderfer, Zachary Manchester:
Scalable Identification of Partially Observed Systems with Certainty-Equivalent EM. ICML 2020: 6830-6840 - [c100]Andrea Zanette, Alessandro Lazaric, Mykel J. Kochenderfer, Emma Brunskill:
Learning Near Optimal Policies with Low Inherent Bellman Error. ICML 2020: 10978-10989 - [c99]Jean-Raymond Betterton, Daniel Ratner, Samuel Webb, Mykel J. Kochenderfer:
Reinforcement Learning for Adaptive Illumination with X-rays. ICRA 2020: 328-334 - [c98]Kyle Brown, Oriana Peltzer, Martin A. Sehr, Mac Schwager, Mykel J. Kochenderfer:
Optimal Sequential Task Assignment and Path Finding for Multi-Agent Robotic Assembly Planning. ICRA 2020: 441-447 - [c97]Shushman Choudhury, Kiril Solovey, Mykel J. Kochenderfer, Marco Pavone:
Efficient Large-Scale Multi-Drone Delivery Using Transit Networks. ICRA 2020: 4543-4550 - [c96]Maxime Bouton, Alireza Nakhaei, David Isele, Kikuo Fujimura, Mykel J. Kochenderfer:
Reinforcement Learning with Iterative Reasoning for Merging in Dense Traffic. ITSC 2020: 1-6 - [c95]Anthony Corso, Mykel J. Kochenderfer:
Interpretable Safety Validation for Autonomous Vehicles. ITSC 2020: 1-6 - [c94]Anthony Corso, Ritchie Lee, Mykel J. Kochenderfer:
Scalable Autonomous Vehicle Safety Validation through Dynamic Programming and Scene Decomposition. ITSC 2020: 1-6 - [c93]Kyle D. Julian, Ritchie Lee, Mykel J. Kochenderfer:
Validation of Image-Based Neural Network Controllers through Adaptive Stress Testing. ITSC 2020: 1-7 - [c92]Mark Koren, Mykel J. Kochenderfer:
Adaptive Stress Testing without Domain Heuristics using Go-Explore. ITSC 2020: 1-6 - [c91]Ransalu Senanayake, Maneekwan Toyungyernsub, Mingyu Wang, Mykel J. Kochenderfer, Mac Schwager:
Directional Primitives for Uncertainty-Aware Motion Estimation in Urban Environments. ITSC 2020: 1-6 - [c90]Jayesh K. Gupta, Kunal Menda, Zachary Manchester, Mykel J. Kochenderfer:
Structured Mechanical Models for Robot Learning and Control. L4DC 2020: 328-337 - [c89]Masha Itkina, Boris Ivanovic, Ransalu Senanayake, Mykel J. Kochenderfer, Marco Pavone:
Evidential Sparsification of Multimodal Latent Spaces in Conditional Variational Autoencoders. NeurIPS 2020 - [c88]Jiaxuan You, Xiaobai Ma, Daisy Yi Ding, Mykel J. Kochenderfer, Jure Leskovec:
Handling Missing Data with Graph Representation Learning. NeurIPS 2020 - [c87]Andrea Zanette, Alessandro Lazaric, Mykel J. Kochenderfer, Emma Brunskill:
Provably Efficient Reward-Agnostic Navigation with Linear Value Iteration. NeurIPS 2020 - [c86]Erdem Biyik, Nicolas Huynh, Mykel J. Kochenderfer, Dorsa Sadigh:
Active Preference-Based Gaussian Process Regression for Reward Learning. Robotics: Science and Systems 2020 - [c85]Shushman Choudhury, Jayesh K. Gupta, Mykel J. Kochenderfer, Dorsa Sadigh, Jeannette Bohg:
Dynamic Multi-Robot Task Allocation under Uncertainty and Temporal Constraints. Robotics: Science and Systems 2020 - [c84]Ayan Mukhopadhyay, Kai Wang, Andrew Perrault, Mykel J. Kochenderfer, Milind Tambe, Yevgeniy Vorobeychik:
Robust Spatial-Temporal Incident Prediction. UAI 2020: 360-369 - [d4]Kunal Menda, Jean de Becdelièvre, Jayesh K. Gupta, Ilan Kroo, Mykel John Kochenderfer, Zachary Manchester:
Normalized Stanford Helicopter Dataset. Zenodo, 2020 - [d3]Andrew Weinert, Mykel J. Kochenderfer, Matthew W. M. Edwards:
Airspace-Encounter-Models/em-model-manned-bayes: Initial public release. Version v1.0. Zenodo, 2020 [all versions] - [d2]Andrew Weinert, Mykel J. Kochenderfer, Matthew W. M. Edwards:
Airspace-Encounter-Models/em-model-manned-bayes: Additional models added + minor updates. Version v1.1. Zenodo, 2020 [all versions] - [d1]Andrew Weinert, Mykel J. Kochenderfer, Matthew W. M. Edwards:
Airspace-Encounter-Models/em-model-manned-bayes: BSD-2 License. Version v1.2. Zenodo, 2020 [all versions] - [i119]Maxime Bouton, Jana Tumova, Mykel J. Kochenderfer:
Point-Based Methods for Model Checking in Partially Observable Markov Decision Processes. CoRR abs/2001.03809 (2020) - [i118]Geoffrey Pettet, Ayan Mukhopadhyay, Mykel J. Kochenderfer, Yevgeniy Vorobeychik, Abhishek Dubey:
On Algorithmic Decision Procedures in Emergency Response Systems in Smart and Connected Communities. CoRR abs/2001.07362 (2020) - [i117]Andrea Zanette, Alessandro Lazaric, Mykel J. Kochenderfer, Emma Brunskill:
Learning Near Optimal Policies with Low Inherent Bellman Error. CoRR abs/2003.00153 (2020) - [i116]Kyle D. Julian, Ritchie Lee, Mykel J. Kochenderfer:
Validation of Image-Based Neural Network Controllers through Adaptive Stress Testing. CoRR abs/2003.02381 (2020) - [i115]John Mern, Dorsa Sadigh, Mykel J. Kochenderfer:
Exchangeable Input Representations for Reinforcement Learning. CoRR abs/2003.09022 (2020) - [i114]Shushman Choudhury, Nate Gruver, Mykel J. Kochenderfer:
Adaptive Informative Path Planning with Multimodal Sensing. CoRR abs/2003.09746 (2020) - [i113]Mark Koren, Mykel J. Kochenderfer:
Adaptive Stress Testing without Domain Heuristics using Go-Explore. CoRR abs/2004.04292 (2020) - [i112]Mark Koren, Anthony Corso, Mykel J. Kochenderfer:
The Adaptive Stress Testing Formulation. CoRR abs/2004.04293 (2020) - [i111]Anthony Corso, Ritchie Lee, Mykel J. Kochenderfer:
Scalable Autonomous Vehicle Safety Validation through Dynamic Programming and Scene Decomposition. CoRR abs/2004.06801 (2020) - [i110]Anthony Corso, Mykel J. Kochenderfer:
Interpretable Safety Validation for Autonomous Vehicles. CoRR abs/2004.06805 (2020) - [i109]Oriana Peltzer, Kyle Brown, Mac Schwager, Mykel J. Kochenderfer, Martin A. Sehr:
STT-CBS: A Conflict-Based Search Algorithm for Multi-Agent Path Finding with Stochastic Travel Times. CoRR abs/2004.08025 (2020) - [i108]Jayesh K. Gupta, Kunal Menda, Zachary Manchester, Mykel J. Kochenderfer:
Structured Mechanical Models for Robot Learning and Control. CoRR abs/2004.10301 (2020) - [i107]Erdem Biyik, Nicolas Huynh, Mykel J. Kochenderfer, Dorsa Sadigh:
Active Preference-Based Gaussian Process Regression for Reward Learning. CoRR abs/2005.02575 (2020) - [i106]Raunak P. Bhattacharyya, Ransalu Senanayake, Kyle Brown, Mykel J. Kochenderfer:
Online Parameter Estimation for Human Driver Behavior Prediction. CoRR abs/2005.02597 (2020) - [i105]Anthony Corso, Robert J. Moss, Mark Koren, Ritchie Lee, Mykel J. Kochenderfer:
A Survey of Algorithms for Black-Box Safety Validation. CoRR abs/2005.02979 (2020) - [i104]Maxime Bouton, Alireza Nakhaei, David Isele, Kikuo Fujimura, Mykel J. Kochenderfer:
Reinforcement Learning with Iterative Reasoning for Merging in Dense Traffic. CoRR abs/2005.11895 (2020) - [i103]Shushman Choudhury, Jayesh K. Gupta, Mykel J. Kochenderfer, Dorsa Sadigh, Jeannette Bohg:
Dynamic Multi-Robot Task Allocation under Uncertainty and Temporal Constraints. CoRR abs/2005.13109 (2020) - [i102]Zachary Sunberg, Mykel J. Kochenderfer:
Improving Automated Driving through Planning with Human Internal States. CoRR abs/2005.14549 (2020) - [i101]Ayan Mukhopadhyay, Geoffrey Pettet, Sayyed Vazirizade, Yevgeniy Vorobeychik, Mykel J. Kochenderfer, Abhishek Dubey:
A Review of Emergency Incident Prediction, Resource Allocation and Dispatch Models. CoRR abs/2006.04200 (2020) - [i100]Raunak P. Bhattacharyya, Blake Wulfe, Derek J. Phillips, Alex Kuefler, Jeremy Morton, Ransalu Senanayake, Mykel J. Kochenderfer:
Modeling Human Driving Behavior through Generative Adversarial Imitation Learning. CoRR abs/2006.06412 (2020) - [i99]Kyle Brown, Katherine Rose Driggs-Campbell, Mykel J. Kochenderfer:
Modeling and Prediction of Human Driver Behavior: A Survey. CoRR abs/2006.08832 (2020) - [i98]Kyle Brown, Oriana Peltzer, Martin A. Sehr, Mac Schwager, Mykel J. Kochenderfer:
Optimal Sequential Task Assignment and Path Finding for Multi-Agent Robotic Assembly Planning. CoRR abs/2006.08845 (2020) - [i97]John Mern, Peter Morales, Mykel J. Kochenderfer:
Towards Recurrent Autoregressive Flow Models. CoRR abs/2006.10096 (2020) - [i96]Sheng Li, Jayesh K. Gupta, Peter Morales, Ross E. Allen, Mykel J. Kochenderfer:
Deep Implicit Coordination Graphs for Multi-agent Reinforcement Learning. CoRR abs/2006.11438 (2020) - [i95]Kunal Menda, Jean de Becdelièvre, Jayesh K. Gupta, Ilan Kroo, Mykel J. Kochenderfer, Zachary Manchester:
Scalable Identification of Partially Observed Systems with Certainty-Equivalent EM. CoRR abs/2006.11615 (2020) - [i94]Ransalu Senanayake, Maneekwan Toyungyernsub, Mingyu Wang, Mykel J. Kochenderfer, Mac Schwager:
Directional Primitives for Uncertainty-Aware Motion Estimation in Urban Environments. CoRR abs/2007.00161 (2020) - [i93]Sheng Li, Maxim Egorov, Mykel J. Kochenderfer:
Analysis of Fleet Management and Network Design for On-Demand Urban Air Mobility Operations. CoRR abs/2008.05535 (2020) - [i92]Andrea Zanette, Alessandro Lazaric, Mykel J. Kochenderfer, Emma Brunskill:
Provably Efficient Reward-Agnostic Navigation with Linear Value Iteration. CoRR abs/2008.07737 (2020) - [i91]Duncan Eddy, Mykel J. Kochenderfer:
A Maximum Independent Set Method for Scheduling Earth Observing Satellite Constellations. CoRR abs/2008.08446 (2020) - [i90]Christopher A. Strong, Haoze Wu, Aleksandar Zeljic, Kyle D. Julian, Guy Katz, Clark W. Barrett, Mykel J. Kochenderfer:
Global Optimization of Objective Functions Represented by ReLU Networks. CoRR abs/2010.03258 (2020) - [i89]John Mern, Anil Yildiz, Zachary Sunberg, Tapan Mukerji, Mykel J. Kochenderfer:
Bayesian Optimized Monte Carlo Planning. CoRR abs/2010.03597 (2020) - [i88]John Mern, Anil Yildiz, Larry Bush, Tapan Mukerji, Mykel J. Kochenderfer:
Improved POMDP Tree Search Planning with Prioritized Action Branching. CoRR abs/2010.03599 (2020) - [i87]Ayan Mukhopadhyay, Geoffrey Pettet, Mykel J. Kochenderfer, Abhishek Dubey:
Designing Emergency Response Pipelines : Lessons and Challenges. CoRR abs/2010.07504 (2020) - [i86]Tina Diao, Samriddhi Singla, Ayan Mukhopadhyay, Ahmed Eldawy, Ross D. Shachter, Mykel J. Kochenderfer:
Uncertainty Aware Wildfire Management. CoRR abs/2010.07915 (2020) - [i85]Masha Itkina, Boris Ivanovic, Ransalu Senanayake, Mykel J. Kochenderfer, Marco Pavone:
Evidential Sparsification of Multimodal Latent Spaces in Conditional Variational Autoencoders. CoRR abs/2010.09164 (2020) - [i84]Bernard Lange, Masha Itkina, Mykel J. Kochenderfer:
Attention Augmented ConvLSTM forEnvironment Prediction. CoRR abs/2010.09662 (2020) - [i83]Christopher Lazarus, James G. Lopez, Mykel J. Kochenderfer:
Runtime Safety Assurance Using Reinforcement Learning. CoRR abs/2010.10618 (2020) - [i82]Jiaxuan You, Xiaobai Ma, Daisy Yi Ding, Mykel J. Kochenderfer, Jure Leskovec:
Handling Missing Data with Graph Representation Learning. CoRR abs/2010.16418 (2020) - [i81]Julia Nitsch, Masha Itkina, Ransalu Senanayake, Juan I. Nieto, Max Schmidt, Roland Siegwart, Mykel J. Kochenderfer, Cesar Cadena:
Out-of-Distribution Detection for Automotive Perception. CoRR abs/2011.01413 (2020) - [i80]Robert J. Moss, Ritchie Lee, Nicholas Visser, Joachim Hochwarth, James G. Lopez, Mykel J. Kochenderfer:
Adaptive Stress Testing of Trajectory Predictions in Flight Management Systems. CoRR abs/2011.02559 (2020) - [i79]Xiaobai Ma, Jiachen Li, Mykel J. Kochenderfer, David Isele, Kikuo Fujimura:
Reinforcement Learning for Autonomous Driving with Latent State Inference and Spatial-Temporal Relationships. CoRR abs/2011.04251 (2020) - [i78]Maneekwan Toyungyernsub, Masha Itkina, Ransalu Senanayake, Mykel J. Kochenderfer:
Double-Prong ConvLSTM for Spatiotemporal Occupancy Prediction in Dynamic Environments. CoRR abs/2011.09045 (2020) - [i77]Kyle Hatch, John Mern, Mykel J. Kochenderfer:
Obstacle Avoidance Using a Monocular Camera. CoRR abs/2012.01608 (2020) - [i76]Anthony Corso, Mykel J. Kochenderfer:
Transfer Learning for Efficient Iterative Safety Validation. CoRR abs/2012.05336 (2020) - [i75]Geoffrey Pettet, Ayan Mukhopadhyay, Mykel J. Kochenderfer, Abhishek Dubey:
Hierarchical Planning for Resource Allocation in Emergency Response Systems. CoRR abs/2012.13300 (2020)
2010 – 2019
- 2019
- [j19]Maxime Bouton, Kyle D. Julian, Alireza Nakhaei, Kikuo Fujimura, Mykel J. Kochenderfer:
Decomposition methods with deep corrections for reinforcement learning. Auton. Agents Multi Agent Syst. 33(3): 330-352 (2019) - [j18]Louis Dressel, Mykel J. Kochenderfer:
Tutorial on the generation of ergodic trajectories with projection-based gradient descent. IET Cyper-Phys. Syst.: Theory & Appl. 4(2): 89-100 (2019) - [j17]Edward Balaban, Stephen B. Johnson, Mykel J. Kochenderfer:
Unifying System Health Management and Automated Decision Making. J. Artif. Intell. Res. 65: 487-518 (2019) - [j16]Kevin T. Carlberg, Antony Jameson, Mykel J. Kochenderfer, Jeremy Morton, Liqian Peng, Freddie D. Witherden:
Recovering missing CFD data for high-order discretizations using deep neural networks and dynamics learning. J. Comput. Phys. 395: 105-124 (2019) - [j15]Kunal Menda, Yi-Chun Chen, Justin Grana, James W. Bono, Brendan D. Tracey, Mykel J. Kochenderfer, David H. Wolpert:
Deep Reinforcement Learning for Event-Driven Multi-Agent Decision Processes. IEEE Trans. Intell. Transp. Syst. 20(4): 1259-1268 (2019) - [j14]Shane T. Barratt, Mykel J. Kochenderfer, Stephen P. Boyd:
Learning Probabilistic Trajectory Models of Aircraft in Terminal Airspace From Position Data. IEEE Trans. Intell. Transp. Syst. 20(9): 3536-3545 (2019) - [j13]Sarah M. Thornton, Benjamin Limonchik, Francis E. Lewis, Mykel J. Kochenderfer, J. Christian Gerdes:
Toward Closing the Loop on Human Values. IEEE Trans. Intell. Veh. 4(3): 437-446 (2019) - [c83]Bohan Wu, Jayesh K. Gupta, Mykel J. Kochenderfer:
Model Primitive Hierarchical Lifelong Reinforcement Learning. AAMAS 2019: 34-42 - [c82]John Mern, Dorsa Sadigh, Mykel J. Kochenderfer:
Object Exchangability in Reinforcement Learning. AAMAS 2019: 2126-2128 - [c81]Guy Katz, Derek A. Huang, Duligur Ibeling, Kyle Julian, Christopher Lazarus, Rachel Lim, Parth Shah, Shantanu Thakoor, Haoze Wu, Aleksandar Zeljic, David L. Dill, Mykel J. Kochenderfer, Clark W. Barrett:
The Marabou Framework for Verification and Analysis of Deep Neural Networks. CAV (1) 2019: 443-452 - [c80]Arec L. Jamgochian, Mykel J. Kochenderfer:
Stochastic Model Predictive Control for Scheduling Charging of Electric Vehicle Fleets with Market Power. ICCVE 2019: 1-6 - [c79]Raunak P. Bhattacharyya, Derek J. Phillips, Changliu Liu, Jayesh K. Gupta, Katherine Rose Driggs-Campbell, Mykel J. Kochenderfer:
Simulating Emergent Properties of Human Driving Behavior Using Multi-Agent Reward Augmented Imitation Learning. ICRA 2019: 789-795 - [c78]Louis Dressel, Mykel J. Kochenderfer:
Hunting Drones with Other Drones: Tracking a Moving Radio Target. ICRA 2019: 1905-1912 - [c77]Michael Kelly, Chelsea Sidrane, Katherine Rose Driggs-Campbell, Mykel J. Kochenderfer:
HG-DAgger: Interactive Imitation Learning with Human Experts. ICRA 2019: 8077-8083 - [c76]Xiaobai Ma, Katherine Rose Driggs-Campbell, Zongzhang Zhang, Mykel J. Kochenderfer:
Monte Carlo Tree Search for Policy Optimization. IJCAI 2019: 3116-3122 - [c75]Jeremy Morton, Freddie D. Witherden, Mykel J. Kochenderfer:
Deep Variational Koopman Models: Inferring Koopman Observations for Uncertainty-Aware Dynamics Modeling and Control. IJCAI 2019: 3173-3179 - [c74]Kunal Menda, Katherine Rose Driggs-Campbell, Mykel J. Kochenderfer:
EnsembleDAgger: A Bayesian Approach to Safe Imitation Learning. IROS 2019: 5041-5048 - [c73]Anthony Corso, Peter Du, Katherine Rose Driggs-Campbell, Mykel J. Kochenderfer:
Adaptive Stress Testing with Reward Augmentation for Autonomous Vehicle Validatio. ITSC 2019: 163-168 - [c72]Masha Itkina, Katherine Rose Driggs-Campbell, Mykel J. Kochenderfer:
Dynamic Environment Prediction in Urban Scenes using Recurrent Representation Learning. ITSC 2019: 2052-2059 - [c71]Maxime Bouton, Alireza Nakhaei, Kikuo Fujimura, Mykel J. Kochenderfer:
Cooperation-Aware Reinforcement Learning for Merging in Dense Traffic. ITSC 2019: 3441-3447 - [c70]Mark Koren, Mykel J. Kochenderfer:
Efficient Autonomy Validation in Simulation with Adaptive Stress Testing. ITSC 2019: 4178-4183 - [c69]Markus Schratter, Maxime Bouton, Mykel J. Kochenderfer, Daniel Watzenig:
Pedestrian Collision Avoidance System for Scenarios with Occlusions. IV 2019: 1054-1060 - [c68]Maxime Bouton, Alireza Nakhaei, Kikuo Fujimura, Mykel J. Kochenderfer:
Safe Reinforcement Learning with Scene Decomposition for Navigating Complex Urban Environments. IV 2019: 1469-1476 - [c67]Tim Allan Wheeler, Mykel J. Kochenderfer:
Critical Factor Graph Situation Clusters for Accelerated Automotive Safety Validation. IV 2019: 2133-2139 - [c66]Shushman Choudhury, Jacob P. Knickerbocker, Mykel J. Kochenderfer:
Dynamic Real-time Multimodal Routing with Hierarchical Hybrid Planning. IV 2019: 2397-2404 - [c65]Andrea Zanette, Alessandro Lazaric, Mykel J. Kochenderfer, Emma Brunskill:
Limiting Extrapolation in Linear Approximate Value Iteration. NeurIPS 2019: 5616-5625 - [c64]Andrea Zanette, Mykel J. Kochenderfer, Emma Brunskill:
Almost Horizon-Free Structure-Aware Best Policy Identification with a Generative Model. NeurIPS 2019: 5626-5635 - [i74]Derek J. Phillips, Juan Carlos Aragon, Anjali Roychowdhury, Regina Madigan, Sunil Chintakindi, Mykel J. Kochenderfer:
Real-time Prediction of Automotive Collision Risk from Monocular Video. CoRR abs/1902.01293 (2019) - [i73]Shushman Choudhury, Mykel J. Kochenderfer:
Dynamic Real-time Multimodal Routing with Hierarchical Hybrid Planning. CoRR abs/1902.01560 (2019) - [i72]Mark Koren, Saud Alsaif, Ritchie Lee, Mykel J. Kochenderfer:
Adaptive Stress Testing for Autonomous Vehicles. CoRR abs/1902.01909 (2019) - [i71]Jayesh K. Gupta, Kunal Menda, Zachary Manchester, Mykel J. Kochenderfer:
A General Framework for Structured Learning of Mechanical Systems. CoRR abs/1902.08705 (2019) - [i70]Jeremy Morton, Freddie D. Witherden, Mykel J. Kochenderfer:
Deep Variational Koopman Models: Inferring Koopman Observations for Uncertainty-Aware Dynamics Modeling and Control. CoRR abs/1902.09742 (2019) - [i69]Kyle D. Julian, Mykel J. Kochenderfer:
A Reachability Method for Verifying Dynamical Systems with Deep Neural Network Controllers. CoRR abs/1903.00520 (2019) - [i68]Kyle D. Julian, Shivam Sharma, Jean-Baptiste Jeannin, Mykel J. Kochenderfer:
Verifying Aircraft Collision Avoidance Neural Networks Through Linear Approximations of Safe Regions. CoRR abs/1903.00762 (2019) - [i67]Bohan Wu, Jayesh K. Gupta, Mykel J. Kochenderfer:
Model Primitive Hierarchical Lifelong Reinforcement Learning. CoRR abs/1903.01567 (2019) - [i66]Xiaobai Ma, Katherine Rose Driggs-Campbell, Mykel J. Kochenderfer:
Improved Robustness and Safety for Autonomous Vehicle Control with Adversarial Reinforcement Learning. CoRR abs/1903.03642 (2019) - [i65]Edward Balaban, Stephen B. Johnson, Mykel J. Kochenderfer:
Rethinking System Health Management. CoRR abs/1903.03948 (2019) - [i64]Raunak P. Bhattacharyya, Derek J. Phillips, Changliu Liu, Jayesh K. Gupta, Katherine Rose Driggs-Campbell, Mykel J. Kochenderfer:
Simulating Emergent Properties of Human Driving Behavior Using Multi-Agent Reward Augmented Imitation Learning. CoRR abs/1903.05766 (2019) - [i63]Changliu Liu, Tomer Arnon, Christopher Lazarus, Clark W. Barrett, Mykel J. Kochenderfer:
Algorithms for Verifying Deep Neural Networks. CoRR abs/1903.06758 (2019) - [i62]Maxime Bouton, Jesper Karlsson, Alireza Nakhaei, Kikuo Fujimura, Mykel J. Kochenderfer, Jana Tumova:
Reinforcement Learning with Probabilistic Guarantees for Autonomous Driving. CoRR abs/1904.07189 (2019) - [i61]Maxime Bouton, Alireza Nakhaei, Kikuo Fujimura, Mykel J. Kochenderfer:
Safe Reinforcement Learning with Scene Decomposition for Navigating Complex Urban Environments. CoRR abs/1904.11483 (2019) - [i60]Markus Schratter, Maxime Bouton, Mykel J. Kochenderfer, Daniel Watzenig:
Pedestrian Collision Avoidance System for Scenarios with Occlusions. CoRR abs/1904.11566 (2019) - [i59]Masha Itkina, Katherine Rose Driggs-Campbell, Mykel J. Kochenderfer:
Dynamic Environment Prediction in Urban Scenes using Recurrent Representation Learning. CoRR abs/1904.12374 (2019) - [i58]Duncan Eddy, Mykel J. Kochenderfer:
Satellite Image Tasking Under Orbit Prediction Uncertainty. CoRR abs/1905.01417 (2019) - [i57]Carl-Johan Hoel, Katherine Rose Driggs-Campbell, Krister Wolff, Leo Laine, Mykel J. Kochenderfer:
Combining Planning and Deep Reinforcement Learning in Tactical Decision Making for Autonomous Driving. CoRR abs/1905.02680 (2019) - [i56]John Mern, Dorsa Sadigh, Mykel J. Kochenderfer:
Object Exchangeability in Reinforcement Learning: Extended Abstract. CoRR abs/1905.02698 (2019) - [i55]Shushman Choudhury, Mykel J. Kochenderfer:
Hybrid Planning for Dynamic Multimodal Stochastic Shortest Paths. CoRR abs/1906.09094 (2019) - [i54]Maxime Bouton, Alireza Nakhaei, Kikuo Fujimura, Mykel J. Kochenderfer:
Cooperation-Aware Reinforcement Learning for Merging in Dense Traffic. CoRR abs/1906.11021 (2019) - [i53]Sydney M. Katz, Anne-Claire Le Bihan, Mykel J. Kochenderfer:
Learning an Urban Air Mobility Encounter Model from Expert Preferences. CoRR abs/1907.05575 (2019) - [i52]Mark Koren, Mykel J. Kochenderfer:
Efficient Autonomy Validation in Simulation with Adaptive Stress Testing. CoRR abs/1907.06795 (2019) - [i51]Ross E. Allen, Javona White Bear, Jayesh K. Gupta, Mykel J. Kochenderfer:
Health-Informed Policy Gradients for Multi-Agent Reinforcement Learning. CoRR abs/1908.01022 (2019) - [i50]Anthony Corso, Peter Du, Katherine Rose Driggs-Campbell, Mykel J. Kochenderfer:
Adaptive Stress Testing with Reward Augmentation for Autonomous Vehicle Validation. CoRR abs/1908.01046 (2019) - [i49]Shushman Choudhury, Kiril Solovey, Mykel J. Kochenderfer, Marco Pavone:
Efficient Large-Scale Multi-Drone Delivery Using Transit Networks. CoRR abs/1909.11840 (2019) - [i48]Duncan Eddy, Mykel J. Kochenderfer:
Markov Decision Processes For Multi-Objective Satellite Task Planning. CoRR abs/1910.08419 (2019) - [i47]Jeremy Morton, Freddie D. Witherden, Mykel J. Kochenderfer:
Parameter-Conditioned Sequential Generative Modeling of Fluid Flows. CoRR abs/1912.06752 (2019) - [i46]Kyle D. Julian, Mykel J. Kochenderfer:
Guaranteeing Safety for Neural Network-Based Aircraft Collision Avoidance Systems. CoRR abs/1912.07084 (2019) - [i45]Sheng Li, Maxim Egorov, Mykel J. Kochenderfer:
Optimizing Collision Avoidance in Dense Airspace using Deep Reinforcement Learning. CoRR abs/1912.10146 (2019) - [i44]Xiaobai Ma, Katherine Rose Driggs-Campbell, Zongzhang Zhang, Mykel J. Kochenderfer:
Monte-Carlo Tree Search for Policy Optimization. CoRR abs/1912.10648 (2019) - 2018
- [j12]Rachael E. Tompa, Blake Wulfe, Mykel J. Kochenderfer, Michael P. Owen:
Horizontal Maneuver Coordination for Aircraft Collision-Avoidance Systems. J. Aerosp. Inf. Syst. 15(2): 92-106 (2018) - [j11]Jeremy Morton, Tim Allan Wheeler, Mykel J. Kochenderfer:
Closed-Loop Policies for Operational Tests of Safety-Critical Systems. IEEE Trans. Intell. Veh. 3(3): 317-328 (2018) - [c63]Zachary N. Sunberg, Mykel J. Kochenderfer:
Online Algorithms for POMDPs with Continuous State, Action, and Observation Spaces. ICAPS 2018: 259-263 - [c62]Louis Dressel, Mykel J. Kochenderfer:
On the Optimality of Ergodic Trajectories for Information Gathering Tasks. ACC 2018: 1855-1861 - [c61]Maxime Bouton, Kyle Julian, Alireza Nakhaei, Kikuo Fujimura, Mykel J. Kochenderfer:
Utility Decomposition with Deep Corrections for Scalable Planning under Uncertainty. AAMAS 2018: 462-469 - [c60]Alex Kuefler, Mykel J. Kochenderfer:
Burn-In Demonstrations for Multi-Modal Imitation Learning. AAMAS 2018: 1071-1078 - [c59]Blake Wulfe, Sunil Chintakindi, Sou-Cheng T. Choi, Rory Hartong-Redden, Anuradha Kodali, Mykel J. Kochenderfer:
Real-Time Prediction of Intermediate-Horizon Automotive Collision Risk. AAMAS 2018: 1087-1096 - [c58]Pol Rosello, Mykel J. Kochenderfer:
Multi-Agent Reinforcement Learning for Multi-Object Tracking. AAMAS 2018: 1397-1404 - [c57]Louis Dressel, Mykel J. Kochenderfer:
Using Neural Networks to Generate Information Maps for Mobile Sensors. CDC 2018: 2555-2560 - [c56]Rui Shu, Shengjia Zhao, Mykel J. Kochenderfer:
Rethinking Style and Content Disentanglement in Variational Autoencoders. ICLR (Workshop) 2018 - [c55]Maxime Bouton, Alireza Nakhaei, Kikuo Fujimura, Mykel J. Kochenderfer:
Scalable Decision Making with Sensor Occlusions for Autonomous Driving. ICRA 2018: 2076-2081 - [c54]Louis Dressel, Mykel J. Kochenderfer:
Pseudo-bearing Measurements for Improved Localization of Radio Sources with Multirotor UAVs. ICRA 2018: 6560-6565 - [c53]Raunak P. Bhattacharyya, Derek J. Phillips, Blake Wulfe, Jeremy Morton, Alex Kuefler, Mykel J. Kochenderfer:
Multi-Agent Imitation Learning for Driving Simulation. IROS 2018: 1534-1539 - [c52]Oladapo Afolabi, Katherine Rose Driggs-Campbell, Roy Dong, Mykel J. Kochenderfer, S. Shankar Sastry:
People as Sensors: Imputing Maps from Human Actions. IROS 2018: 2342-2348 - [c51]Yi-Chun Chen, Mykel J. Kochenderfer, Matthijs T. J. Spaan:
Improving Offline Value-Function Approximations for POMDPs by Reducing Discount Factors. IROS 2018: 3531-3536 - [c50]Julie M. Walker, Allison M. Okamura, Mykel J. Kochenderfer:
Gaussian Process Dynamic Programming for Optimizing Ungrounded Haptic Guidance. IROS 2018: 8758-8764 - [c49]Changliu Liu, Mykel J. Kochenderfer:
Analytically Modeling Unmanaged Intersections with Microscopic Vehicle Interactions. ITSC 2018: 2352-2357 - [c48]Chelsea Sidrane, Mykel J. Kochenderfer:
Closed-Loop Planning for Disaster Evacuation with Stochastic Arrivals. ITSC 2018: 2544-2549 - [c47]Mark Koren, Saud Alsaif, Ritchie Lee, Mykel J. Kochenderfer:
Adaptive Stress Testing for Autonomous Vehicles. Intelligent Vehicles Symposium 2018: 1-7 - [c46]Sarah M. Thornton, Francis E. Lewis, Vivian Zhang, Mykel J. Kochenderfer, J. Christian Gerdes:
Value Sensitive Design for Autonomous Vehicle Motion Planning. Intelligent Vehicles Symposium 2018: 1157-1162 - [c45]Xiaobai Ma, Katherine Rose Driggs-Campbell, Mykel J. Kochenderfer:
Improved Robustness and Safety for Autonomous Vehicle Control with Adversarial Reinforcement Learning. Intelligent Vehicles Symposium 2018: 1665-1671 - [c44]Ekhlas Sonu, Zachary Sunberg, Mykel J. Kochenderfer:
Exploiting Hierarchy for Scalable Decision Making in Autonomous Driving. Intelligent Vehicles Symposium 2018: 2203-2208 - [c43]Rui Shu, Hung H. Bui, Shengjia Zhao, Mykel J. Kochenderfer, Stefano Ermon:
Amortized Inference Regularization. NeurIPS 2018: 4398-4407 - [c42]Jeremy Morton, Antony Jameson, Mykel J. Kochenderfer, Freddie D. Witherden:
Deep Dynamical Modeling and Control of Unsteady Fluid Flows. NeurIPS 2018: 9278-9288 - [c41]Andrea Zanette, Junzi Zhang, Mykel J. Kochenderfer:
Robust Super-Level Set Estimation Using Gaussian Processes. ECML/PKDD (2) 2018: 276-291 - [c40]Ritchie Lee, Mykel J. Kochenderfer, Ole J. Mengshoel, Joshua Silbermann:
Interpretable Categorization of Heterogeneous Time Series Data. SDM 2018: 216-224 - [i43]Lindsey Kuper, Guy Katz, Justin Gottschlich, Kyle Julian, Clark W. Barrett, Mykel J. Kochenderfer:
Toward Scalable Verification for Safety-Critical Deep Networks. CoRR abs/1801.05950 (2018) - [i42]Blake Wulfe, Sunil Chintakindi, Sou-Cheng T. Choi, Rory Hartong-Redden, Anuradha Kodali, Mykel J. Kochenderfer:
Real-time Prediction of Intermediate-Horizon Automotive Collision Risk. CoRR abs/1802.01532 (2018) - [i41]Maxime Bouton, Kyle Julian, Alireza Nakhaei, Kikuo Fujimura, Mykel J. Kochenderfer:
Utility Decomposition with Deep Corrections for Scalable Planning under Uncertainty. CoRR abs/1802.01772 (2018) - [i40]John Mern, Jayesh K. Gupta, Mykel J. Kochenderfer:
Layer-wise synapse optimization for implementing neural networks on general neuromorphic architectures. CoRR abs/1802.06920 (2018) - [i39]Raunak P. Bhattacharyya, Derek J. Phillips, Blake Wulfe, Jeremy Morton, Alex Kuefler, Mykel J. Kochenderfer:
Multi-Agent Imitation Learning for Driving Simulation. CoRR abs/1803.01044 (2018) - [i38]Changliu Liu, Mykel J. Kochenderfer:
Analytically Modeling Unmanaged Intersections with Microscopic Vehicle Interactions. CoRR abs/1804.04746 (2018) - [i37]Jeremy Morton, Freddie D. Witherden, Antony Jameson, Mykel J. Kochenderfer:
Deep Dynamical Modeling and Control of Unsteady Fluid Flows. CoRR abs/1805.07472 (2018) - [i36]Rui Shu, Hung H. Bui, Shengjia Zhao, Mykel J. Kochenderfer, Stefano Ermon:
Amortized Inference Regularization. CoRR abs/1805.08913 (2018) - [i35]Changliu Liu, Mykel J. Kochenderfer:
Analyzing Traffic Delay at Unmanaged Intersections. CoRR abs/1806.02660 (2018) - [i34]Kunal Menda, Katherine Rose Driggs-Campbell, Mykel J. Kochenderfer:
EnsembleDAgger: A Bayesian Approach to Safe Imitation Learning. CoRR abs/1807.08364 (2018) - [i33]Patrick Slade, Zachary N. Sunberg, Mykel J. Kochenderfer:
Estimation and Control Using Sampling-Based Bayesian Reinforcement Learning. CoRR abs/1808.00888 (2018) - [i32]Louis Dressel, Mykel J. Kochenderfer:
Efficient and Low-cost Localization of Radio Signals with a Multirotor UAV. CoRR abs/1808.04438 (2018) - [i31]Louis Dressel, Mykel J. Kochenderfer:
On the Optimality of Ergodic Trajectories for Information Gathering Tasks. CoRR abs/1808.06652 (2018) - [i30]Louis Dressel, Mykel J. Kochenderfer:
Using Neural Networks to Generate Information Maps for Mobile Sensors. CoRR abs/1809.10012 (2018) - [i29]Kyle D. Julian, Mykel J. Kochenderfer:
Image-based Guidance of Autonomous Aircraft for Wildfire Surveillance and Prediction. CoRR abs/1810.02455 (2018) - [i28]Michael Kelly, Chelsea Sidrane, Katherine Rose Driggs-Campbell, Mykel J. Kochenderfer:
HG-DAgger: Interactive Imitation Learning with Human Experts. CoRR abs/1810.02890 (2018) - [i27]Kyle D. Julian, Mykel J. Kochenderfer, Michael P. Owen:
Deep Neural Network Compression for Aircraft Collision Avoidance Systems. CoRR abs/1810.04240 (2018) - [i26]Kyle D. Julian, Mykel J. Kochenderfer:
Distributed Wildfire Surveillance with Autonomous Aircraft using Deep Reinforcement Learning. CoRR abs/1810.04244 (2018) - [i25]Shane T. Barratt, Mykel J. Kochenderfer, Stephen P. Boyd:
Learning Probabilistic Trajectory Models of Aircraft in Terminal Airspace from Position Data. CoRR abs/1810.09568 (2018) - [i24]Ritchie Lee, Ole J. Mengshoel, Anshu Saksena, Ryan W. Gardner, Daniel Genin, Joshua Silbermann, Michael P. Owen, Mykel J. Kochenderfer:
Adaptive Stress Testing: Finding Failure Events with Reinforcement Learning. CoRR abs/1811.02188 (2018) - [i23]Andrea Zanette, Junzi Zhang, Mykel J. Kochenderfer:
Robust Super-Level Set Estimation using Gaussian Processes. CoRR abs/1811.09977 (2018) - [i22]Kevin T. Carlberg, Antony Jameson, Mykel J. Kochenderfer, Jeremy Morton, Liqian Peng, Freddie D. Witherden:
Recovering missing CFD data for high-order discretizations using deep neural networks and dynamics learning. CoRR abs/1812.01177 (2018) - [i21]John Mern, Kyle Julian, Rachael E. Tompa, Mykel J. Kochenderfer:
Visual Depth Mapping from Monocular Images using Recurrent Convolutional Neural Networks. CoRR abs/1812.04082 (2018) - 2017
- [j10]Dimitris Bertsimas, J. Daniel Griffith, Vishal Gupta, Mykel J. Kochenderfer, Velibor V. Misic:
A comparison of Monte Carlo tree search and rolling horizon optimization for large-scale dynamic resource allocation problems. Eur. J. Oper. Res. 263(2): 664-678 (2017) - [j9]Yi-Chun Chen, Tim Allan Wheeler, Mykel J. Kochenderfer:
Learning Discrete Bayesian Networks from Continuous Data. J. Artif. Intell. Res. 59: 103-132 (2017) - [j8]Maxim Egorov, Zachary N. Sunberg, Edward Balaban, Tim Allan Wheeler, Jayesh K. Gupta, Mykel J. Kochenderfer:
POMDPs.jl: A Framework for Sequential Decision Making under Uncertainty. J. Mach. Learn. Res. 18: 26:1-26:5 (2017) - [j7]Zouhair Mahboubi, Mykel J. Kochenderfer:
Learning Traffic Patterns at Small Airports From Flight Tracks. IEEE Trans. Intell. Transp. Syst. 18(4): 917-926 (2017) - [j6]Jeremy Morton, Tim Allan Wheeler, Mykel J. Kochenderfer:
Analysis of Recurrent Neural Networks for Probabilistic Modeling of Driver Behavior. IEEE Trans. Intell. Transp. Syst. 18(5): 1289-1298 (2017) - [c39]Louis Dressel, Mykel J. Kochenderfer:
Efficient Decision-Theoretic Target Localization. ICAPS 2017: 70-78 - [c38]Zachary N. Sunberg, Christopher J. Ho, Mykel J. Kochenderfer:
The value of inferring the internal state of traffic participants for autonomous freeway driving. ACC 2017: 3004-3010 - [c37]Jayesh K. Gupta, Maxim Egorov, Mykel J. Kochenderfer:
Cooperative Multi-agent Control Using Deep Reinforcement Learning. AAMAS Workshops (Selected Papers) 2017: 66-83 - [c36]Guy Katz, Clark W. Barrett, David L. Dill, Kyle Julian, Mykel J. Kochenderfer:
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks. CAV (1) 2017: 97-117 - [c35]Alex Kuefler, Mykel J. Kochenderfer, James L. McClelland:
Geometric Concept Acquisition in a Dueling Deep Q-Network. CogSci 2017 - [c34]Zongzhang Zhang, Zhiyuan Pan, Mykel J. Kochenderfer:
Weighted Double Q-learning. IJCAI 2017: 3455-3461 - [c33]Patrick Slade, Preston Culbertson, Zachary Sunberg, Mykel J. Kochenderfer:
Simultaneous active parameter estimation and control using sampling-based Bayesian reinforcement learning. IROS 2017: 804-810 - [c32]Jeremy Morton, Mykel J. Kochenderfer:
Simultaneous policy learning and latent state inference for imitating driver behavior. ITSC 2017: 1-6 - [c31]Tim Allan Wheeler, Martin Holder, Hermann Winner, Mykel J. Kochenderfer:
Deep stochastic radar models. Intelligent Vehicles Symposium 2017: 47-53 - [c30]Alex Kuefler, Jeremy Morton, Tim Allan Wheeler, Mykel J. Kochenderfer:
Imitating driver behavior with generative adversarial networks. Intelligent Vehicles Symposium 2017: 204-211 - [c29]Maxime Bouton, Akansel Cosgun, Mykel J. Kochenderfer:
Belief state planning for autonomously navigating urban intersections. Intelligent Vehicles Symposium 2017: 825-830 - [c28]Derek J. Phillips, Tim Allan Wheeler, Mykel J. Kochenderfer:
Generalizable intention prediction of human drivers at intersections. Intelligent Vehicles Symposium 2017: 1665-1670 - [c27]John Mern, Jayesh K. Gupta, Mykel J. Kochenderfer:
Layer-wise synapse optimization for implementing neural networks on general neuromorphic architectures. SSCI 2017: 1-8 - [c26]Youngjun Kim, Yonatan Gur, Mykel J. Kochenderfer:
Heuristics for planning with rare catastrophic events. WSC 2017: 3030-3041 - [c25]Guy Katz, Clark W. Barrett, David L. Dill, Kyle Julian, Mykel J. Kochenderfer:
Towards Proving the Adversarial Robustness of Deep Neural Networks. FVAV@iFM 2017: 19-26 - [i20]Alex Kuefler, Jeremy Morton, Tim Allan Wheeler, Mykel John Kochenderfer:
Imitating Driver Behavior with Generative Adversarial Networks. CoRR abs/1701.06699 (2017) - [i19]Tim Allan Wheeler, Martin Holder, Hermann Winner, Mykel J. Kochenderfer:
Deep Stochastic Radar Models. CoRR abs/1701.09180 (2017) - [i18]Zachary Sunberg, Christopher Ho, Mykel J. Kochenderfer:
The Value of Inferring the Internal State of Traffic Participants for Autonomous Freeway Driving. CoRR abs/1702.00858 (2017) - [i17]Guy Katz, Clark W. Barrett, David L. Dill, Kyle Julian, Mykel J. Kochenderfer:
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks. CoRR abs/1702.01135 (2017) - [i16]Maxime Bouton, Akansel Cosgun, Mykel J. Kochenderfer:
Belief State Planning for Autonomously Navigating Urban Intersections. CoRR abs/1704.04322 (2017) - [i15]Jeremy Morton, Mykel J. Kochenderfer:
Simultaneous Policy Learning and Latent State Inference for Imitating Driver Behavior. CoRR abs/1704.05566 (2017) - [i14]Jeremy Morton, Tim Allan Wheeler, Mykel J. Kochenderfer:
Optimal Testing of Self-Driving Cars. CoRR abs/1707.08234 (2017) - [i13]Patrick Slade, Preston Culbertson, Zachary Sunberg, Mykel J. Kochenderfer:
Simultaneous active parameter estimation and control using sampling-based Bayesian reinforcement learning. CoRR abs/1707.09055 (2017) - [i12]Ritchie Lee, Mykel J. Kochenderfer, Ole J. Mengshoel, Joshua Silbermann:
Interpretable Categorization of Heterogeneous Time Series Data. CoRR abs/1708.09121 (2017) - [i11]Kunal Menda, Katherine Rose Driggs-Campbell, Mykel J. Kochenderfer:
DropoutDAgger: A Bayesian Approach to Safe Imitation Learning. CoRR abs/1709.06166 (2017) - [i10]Zachary Sunberg, Mykel J. Kochenderfer:
POMCPOW: An online algorithm for POMDPs with continuous state, action, and observation spaces. CoRR abs/1709.06196 (2017) - [i9]Kunal Menda, Yi-Chun Chen, Justin Grana, James W. Bono, Brendan D. Tracey, Mykel J. Kochenderfer, David H. Wolpert:
Deep Reinforcement Learning for Event-Driven Multi-Agent Decision Processes. CoRR abs/1709.06656 (2017) - [i8]Alex Kuefler, Mykel J. Kochenderfer:
Burn-In Demonstrations for Multi-Modal Imitation Learning. CoRR abs/1710.05090 (2017) - [i7]Oladapo Afolabi, Katherine Rose Driggs-Campbell, Roy Dong, Mykel J. Kochenderfer, S. Shankar Sastry:
People as Sensors: Imputing Maps from Human Actions. CoRR abs/1711.01022 (2017) - 2016
- [j5]Jonathan Cox, Mykel J. Kochenderfer:
Ground Delay Program Planning Using Markov Decision Processes. J. Aerosp. Inf. Syst. 13(3): 134-142 (2016) - [c24]Maxim Egorov, Mykel J. Kochenderfer, Jaak J. Uudmae:
Target Surveillance in Adversarial Environments Using POMDPs. AAAI 2016: 2473-2479 - [c23]Philipp Robbel, Frans A. Oliehoek, Mykel J. Kochenderfer:
Exploiting Anonymity in Approximate Linear Programming: Scaling to Large Multiagent MDPs. AAAI 2016: 2537-2543 - [c22]Yegor Tkachenko, Mykel J. Kochenderfer, Krzysztof Kluza:
Customer Simulation for Direct Marketing Experiments. DSAA 2016: 478-487 - [c21]Zachary N. Sunberg, Mykel J. Kochenderfer, Marco Pavone:
Optimized and trusted collision avoidance for unmanned aerial vehicles using approximate dynamic programming. ICRA 2016: 1455-1461 - [c20]Tim Allan Wheeler, Mykel J. Kochenderfer:
Factor graph scene distributions for automotive safety analysis. ITSC 2016: 1035-1040 - [c19]Tim Allan Wheeler, Philipp Robbel, Mykel J. Kochenderfer:
Analysis of microscopic behavior models for probabilistic modeling of driver behavior. ITSC 2016: 1604-1609 - [c18]Vineet Mehta, Paul D. Rowe, Gene Lewis, Ashe Magalhaes, Mykel J. Kochenderfer:
Decision-theoretic approach to designing cyber resilient systems. NCA 2016: 302-309 - [i6]Zachary N. Sunberg, Mykel J. Kochenderfer, Marco Pavone:
Optimized and Trusted Collision Avoidance for Unmanned Aerial Vehicles using Approximate Dynamic Programming (Technical Report). CoRR abs/1602.04762 (2016) - 2015
- [j4]Mykel J. Kochenderfer:
Introduction to the Special Issue on Optimal Decision Making in Aerospace Systems. J. Aerosp. Inf. Syst. 12(10): 617 (2015) - [j3]Kyle A. Smith, Adan E. Vela, Mykel J. Kochenderfer, Wesley A. Olson:
Optimizing a Collision-Avoidance System for Closely Spaced Parallel Operations. J. Aerosp. Inf. Syst. 12(10): 618-633 (2015) - [j2]John R. Lepird, Michael P. Owen, Mykel J. Kochenderfer:
Bayesian Preference Elicitation for Multiobjective Engineering Design Optimization. J. Aerosp. Inf. Syst. 12(10): 634-645 (2015) - [c17]Philipp Robbel, Frans A. Oliehoek, Mykel J. Kochenderfer:
Exploiting Anonymity in Approximate Linear Programming: Scaling to Large Multiagent MDPs. AAAI Fall Symposia 2015: 75-82 - [c16]Zouhair Mahboubi, Mykel J. Kochenderfer:
Continous time autonomous air traffic control for non-towered airports. CDC 2015: 3433-3438 - [c15]Christopher Ho, Mykel J. Kochenderfer, Vineet Mehta, Rajmonda Sulo Caceres:
Control of epidemics on graphs. CDC 2015: 4202-4207 - [c14]Tim Allan Wheeler, Philipp Robbel, Mykel J. Kochenderfer:
A Probabilistic Framework for Microscopic Traffic Propagation. ITSC 2015: 262-267 - [c13]Tim Allan Wheeler, Mykel J. Kochenderfer, Philipp Robbel:
Initial Scene Configurations for Highway Traffic Propagation. ITSC 2015: 279-284 - [i5]Philipp Robbel, Frans A. Oliehoek, Mykel J. Kochenderfer:
Exploiting Anonymity in Approximate Linear Programming: Scaling to Large Multiagent MDPs (Extended Version). CoRR abs/1511.09080 (2015) - [i4]Yi-Chun Chen, Tim Allan Wheeler, Mykel John Kochenderfer:
Learning Discrete Bayesian Networks from Continuous Data. CoRR abs/1512.02406 (2015) - 2014
- [i3]Dimitris Bertsimas, J. Daniel Griffith, Vishal Gupta, Mykel J. Kochenderfer, Velibor V. Misic, Robert J. Moss:
A Comparison of Monte Carlo Tree Search and Mathematical Optimization for Large Scale Dynamic Resource Allocation. CoRR abs/1405.5498 (2014) - [i2]Erik J. Schlicht, Ritchie Lee, David H. Wolpert, Mykel J. Kochenderfer, Brendan D. Tracey:
Predicting the behavior of interacting humans by fusing data from multiple sources. CoRR abs/1408.2053 (2014) - 2013
- [c12]Christopher Amato, Girish Chowdhary, Alborz Geramifard, N. Kemal Ure, Mykel J. Kochenderfer:
Decentralized control of partially observable Markov decision processes. CDC 2013: 2398-2405 - [c11]Mykel J. Kochenderfer, Nicholas Monath:
Compression of Optimal Value Functions for Markov Decision Processes. DCC 2013: 501 - 2012
- [c10]Erik J. Schlicht, Ritchie Lee, David H. Wolpert, Mykel J. Kochenderfer, Brendan D. Tracey:
Predicting the behavior of interacting humans by fusing data from multiple sources. UAI 2012: 756-765 - [i1]Erik J. Schlicht, Ritchie Lee, David H. Wolpert, Mykel J. Kochenderfer, Brendan D. Tracey:
Predicting the behavior of interacting humans by fusing data from multiple sources. CoRR abs/1206.6080 (2012) - 2011
- [j1]Travis B. Wolf, Mykel J. Kochenderfer:
Aircraft Collision Avoidance Using Monte Carlo Real-Time Belief Space Search. J. Intell. Robotic Syst. 64(2): 277-298 (2011) - [c9]James P. Chryssanthacopoulos, Mykel J. Kochenderfer:
Collision avoidance system optimization with probabilistic pilot response models. ACC 2011: 2765-2770 - [c8]Mykel J. Kochenderfer, James P. Chryssanthacopoulos:
Partially-controlled Markov Decision Processes for Collision Avoidance Systems. ICAART (1) 2011: 61-70 - [c7]Mykel J. Kochenderfer, James P. Chryssanthacopoulos:
Collision Avoidance Using Partially Controlled Markov Decision Processes. ICAART (Revised Selected Papers) 2011: 86-100 - [c6]James P. Chryssanthacopoulos, Mykel J. Kochenderfer:
Analysis of open-loop and closed-loop planning for aircraft collision avoidance. ITSC 2011: 212-217 - [c5]Haoyu Bai, David Hsu, Mykel J. Kochenderfer, Wee Sun Lee:
Unmanned Aircraft Collision Avoidance using Continuous-State POMDPs. Robotics: Science and Systems 2011 - 2010
- [c4]Mykel J. Kochenderfer, James P. Chryssanthacopoulos:
A decision-theoretic approach to developing robust collision avoidance logic. ITSC 2010: 1837-1842
2000 – 2009
- 2006
- [b1]Mykel J. Kochenderfer:
Adaptive modelling and planning for learning intelligent behaviour. University of Edinburgh, UK, 2006 - 2005
- [c3]Mykel J. Kochenderfer:
Adaptive Modeling and Planning for Reactive Agents. AAAI 2005: 1648-1649 - 2004
- [c2]Rakesh Gupta, Mykel J. Kochenderfer:
Common Sense Data Acquisition for Indoor Mobile Robots. AAAI 2004: 605-610 - 2003
- [c1]Mykel J. Kochenderfer:
Evolving Hierarchical and Recursive Teleo-reactive Programs through Genetic Programming. EuroGP 2003: 83-92
Coauthor Index
Ali-akbar Agha-mohammadi
aka: Ali-Akbar Agha-Mohammadi
aka: Ali-Akbar Agha-Mohammadi
Katherine Rose Driggs-Campbell
aka: Katherine Driggs Campbell
aka: Katherine Driggs Campbell
Kyle Julian
aka: Kyle D. Julian
aka: Kyle D. Julian
John Mern
aka: John Michael Mern
aka: John Michael Mern
Zachary Sunberg
aka: Zachary N. Sunberg
aka: Zachary N. Sunberg
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