default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDPradeep Varakantham
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2024
[c132]Huy Hoang, Tien Mai, Pradeep Varakantham
:
Imitate the Good and Avoid the Bad: An Incremental Approach to Safe Reinforcement Learning. AAAI 2024: 12439-12447- [c131]Wenjun Li, Pradeep Varakantham:
Unsupervised Training Sequence Design: Efficient and Generalizable Agent Training. AAAI 2024: 13637-13645 - [c130]Hao Jiang, Tien Mai, Pradeep Varakantham, Huy Hoang:
Reward Penalties on Augmented States for Solving Richly Constrained RL Effectively. AAAI 2024: 19867-19875 - [c129]Yuxiao Lu, Arunesh Sinha, Pradeep Varakantham:
Handling Long and Richly Constrained Tasks through Constrained Hierarchical Reinforcement Learning. AAAI 2024: 21368-21377 - [c128]Jayden Teoh Jing Teoh, Wenjun Li, Pradeep Varakantham:
Unifying Regret and State-Action Space Coverage for Effective Unsupervised Environment Design. AAMAS 2024: 2507-2509 - [c127]Roman Belaire, Pradeep Varakantham, Thanh Hong Nguyen, David Lo:
Regret-based Defense in Adversarial Reinforcement Learning. AAMAS 2024: 2633-2640 - [c126]Shashank Reddy Chirra, Pradeep Varakantham, Praveen Paruchuri:
Preserving the Privacy of Reward Functions in MDPs through Deception. ECAI 2024: 2146-2153 - [c125]Qian Shao, Pradeep Varakantham, Shih-Fen Cheng:
Imitating Cost-Constrained Behaviors in Reinforcement Learning. ICAPS 2024: 514-522 - [c124]Gauri Jain, Pradeep Varakantham, Haifeng Xu, Aparna Taneja, Prashant Doshi, Milind Tambe:
IRL for Restless Multi-armed Bandits with Applications in Maternal and Child Health. PRICAI (5) 2024: 165-178 - [i46]Huy Hoang, Tien Mai, Pradeep Varakantham:
SubIQ: Inverse Soft-Q Learning for Offline Imitation with Suboptimal Demonstrations. CoRR abs/2402.13147 (2024) - [i45]Qian Shao, Pradeep Varakantham, Shih-Fen Cheng:
Imitating Cost-Constrained Behaviors in Reinforcement Learning. CoRR abs/2403.17456 (2024) - [i44]Roman Belaire, Arunesh Sinha, Pradeep Varakantham:
Probabilistic Perspectives on Error Minimization in Adversarial Reinforcement Learning. CoRR abs/2406.04724 (2024) - [i43]Changyu Chen, Zichen Liu, Chao Du, Tianyu Pang, Qian Liu, Arunesh Sinha, Pradeep Varakantham, Min Lin:
Bootstrapping Language Models with DPO Implicit Rewards. CoRR abs/2406.09760 (2024) - [i42]Wenjun Li, Changyu Chen, Pradeep Varakantham:
Unlocking Large Language Model's Planning Capabilities with Maximum Diversity Fine-tuning. CoRR abs/2406.10479 (2024) - [i41]Sidney Tio, Dexun Li, Pradeep Varakantham:
EduQate: Generating Adaptive Curricula through RMABs in Education Settings. CoRR abs/2406.14122 (2024) - [i40]Shashank Reddy Chirra, Pradeep Varakantham, Praveen Paruchuri:
Safety through feedback in Constrained RL. CoRR abs/2406.19626 (2024) - [i39]Shashank Reddy Chirra, Pradeep Varakantham, Praveen Paruchuri:
Preserving the Privacy of Reward Functions in MDPs through Deception. CoRR abs/2407.09809 (2024) - [i38]Changyu Chen, Shashank Reddy Chirra, Maria José Ferreira, Cleotilde Gonzalez, Arunesh Sinha, Pradeep Varakantham:
Towards Neural Network based Cognitive Models of Dynamic Decision-Making by Humans. CoRR abs/2407.17622 (2024) - [i37]Huy Hoang, Tien Mai, Pradeep Varakantham:
UNIQ: Offline Inverse Q-learning for Avoiding Undesirable Demonstrations. CoRR abs/2410.08307 (2024) - [i36]Yuxiao Lu, Arunesh Sinha, Pradeep Varakantham:
Semantic Loss Guided Data Efficient Supervised Fine Tuning for Safe Responses in LLMs. CoRR abs/2412.06843 (2024) - [i35]Gauri Jain, Pradeep Varakantham, Haifeng Xu, Aparna Taneja, Prashant Doshi, Milind Tambe:
IRL for Restless Multi-Armed Bandits with Applications in Maternal and Child Health. CoRR abs/2412.08463 (2024) - [i34]Ze Gong, Akshat Kumar, Pradeep Varakantham:
Offline Safe Reinforcement Learning Using Trajectory Classification. CoRR abs/2412.15429 (2024) - 2023
- [c123]Xianjie Zhang, Pradeep Varakantham, Hao Jiang:
Future Aware Pricing and Matching for Sustainable On-Demand Ride Pooling. AAAI 2023: 14628-14636 - [c122]Pathmanathan Pankayaraj, Pradeep Varakantham:
Constrained Reinforcement Learning in Hard Exploration Problems. AAAI 2023: 15055-15063 - [c121]Rajiv Ranjan Kumar, Pradeep Varakantham, Shih-Fen Cheng:
Strategic Planning for Flexible Agent Availability in Large Taxi Fleets. AAMAS 2023: 552-560 - [c120]Jiajing Ling, Moritz Lukas Schuler, Akshat Kumar, Pradeep Varakantham:
Knowledge Compilation for Constrained Combinatorial Action Spaces in Reinforcement Learning. AAMAS 2023: 860-868 - [c119]Dexun Li, Pradeep Varakantham:
Avoiding Starvation of Arms in Restless Multi-Armed Bandits. AAMAS 2023: 1303-1311 - [c118]Avinandan Bose, Hao Jiang, Pradeep Varakantham, Zichang Ge:
On Sustainable Ride Pooling Through Conditional Expected Value Decomposition. ECAI 2023: 295-302 - [c117]Sidney Tio, Pradeep Varakantham:
Transferable Curricula through Difficulty Conditioned Generators. IJCAI 2023: 4883-4891 - [c116]Wenjun Li, Pradeep Varakantham, Dexun Li:
Generalization through Diversity: Improving Unsupervised Environment Design. IJCAI 2023: 5411-5419 - [c115]Changyu Chen, Ramesha Karunasena, Thanh Hong Nguyen, Arunesh Sinha, Pradeep Varakantham:
Generative Modelling of Stochastic Actions with Arbitrary Constraints in Reinforcement Learning. NeurIPS 2023 - [i33]Wenjun Li, Pradeep Varakantham, Dexun Li:
Effective Diversity in Unsupervised Environment Design. CoRR abs/2301.08025 (2023) - [i32]Hao Jiang, Tien Mai, Pradeep Varakantham:
Solving Constrained Reinforcement Learning through Augmented State and Reward Penalties. CoRR abs/2301.11592 (2023) - [i31]Dexun Li, Wenjun Li, Pradeep Varakantham:
Diversity Induced Environment Design via Self-Play. CoRR abs/2302.02119 (2023) - [i30]Roman Belaire, Pradeep Varakantham, David Lo:
Regret-Based Optimization for Robust Reinforcement Learning. CoRR abs/2302.06912 (2023) - [i29]Xianjie Zhang, Pradeep Varakantham, Hao Jiang:
Future Aware Pricing and Matching for Sustainable On-demand Ride Pooling. CoRR abs/2302.10510 (2023) - [i28]Yuxiao Lu, Pradeep Varakantham, Arunesh Sinha:
Conditioning Hierarchical Reinforcement Learning on Flexible Constraints. CoRR abs/2302.10639 (2023) - [i27]Rajiv Ranjan Kumar, Pradeep Varakantham, Shih-Fen Cheng:
Strategic Planning for Flexible Agent Availability in Large Taxi Fleets. CoRR abs/2303.04337 (2023) - [i26]Sidney Tio, Pradeep Varakantham:
Transferable Curricula through Difficulty Conditioned Generators. CoRR abs/2306.13028 (2023) - [i25]Dexun Li, Pradeep Varakantham:
A Hierarchical Approach to Environment Design with Generative Trajectory Modeling. CoRR abs/2310.00301 (2023) - [i24]Changyu Chen, Ramesha Karunasena, Thanh Hong Nguyen, Arunesh Sinha, Pradeep Varakantham:
Generative Modelling of Stochastic Actions with Arbitrary Constraints in Reinforcement Learning. CoRR abs/2311.15341 (2023) - [i23]Sidney Tio, Jimmy Ho, Pradeep Varakantham:
Training Reinforcement Learning Agents and Humans With Difficulty-Conditioned Generators. CoRR abs/2312.02309 (2023) - [i22]Huy Hoang, Tien Mai, Pradeep Varakantham:
Imitate the Good and Avoid the Bad: An Incremental Approach to Safe Reinforcement Learning. CoRR abs/2312.10385 (2023) - 2022
- [c114]Aditya Mate, Lovish Madaan, Aparna Taneja, Neha Madhiwalla, Shresth Verma, Gargi Singh, Aparna Hegde, Pradeep Varakantham, Milind Tambe:
Field Study in Deploying Restless Multi-Armed Bandits: Assisting Non-profits in Improving Maternal and Child Health. AAAI 2022: 12017-12025 - [c113]Susobhan Ghosh, Pradeep Varakantham, Aniket Bhatkhande, Tamanna Ahmad, Anish Andheria, Wenjun Li, Aparna Taneja, Divy Thakkar, Milind Tambe:
Facilitating Human-Wildlife Cohabitation through Conflict Prediction. AAAI 2022: 12496-12502 - [c112]Sanket Shah, Meghna Lowalekar, Pradeep Varakantham:
Joint Pricing and Matching for City-Scale Ride-Pooling. ICAPS 2022: 499-507 - [c111]Sylvie Thiébaux, William Yeoh, Akshat Kumar, Pradeep Varakantham:
Preface. ICAPS 2022 - [c110]Jiang Hao, Pradeep Varakantham:
Hierarchical Value Decomposition for Effective On-demand Ride-Pooling. AAMAS 2022: 580-587 - [c109]Dexun Li, Pradeep Varakantham:
Efficient resource allocation with fairness constraints in restless multi-armed bandits. UAI 2022: 1158-1167 - [e1]Akshat Kumar, Sylvie Thiébaux, Pradeep Varakantham, William Yeoh:
Proceedings of the Thirty-Second International Conference on Automated Planning and Scheduling, ICAPS 2022, Singapore (virtual), June 13-24, 2022. AAAI Press 2022, ISBN 978-1-57735-874-9 [contents] - [i21]Dexun Li, Pradeep Varakantham:
Efficient Resource Allocation with Fairness Constraints in Restless Multi-Armed Bandits. CoRR abs/2206.03883 (2022) - [i20]Dexun Li, Pradeep Varakantham:
Towards Soft Fairness in Restless Multi-Armed Bandits. CoRR abs/2207.13343 (2022) - [i19]Tanvi Verma, Pradeep Varakantham:
Learning Individual Policies in Large Multi-agent Systems through Local Variance Minimization. CoRR abs/2212.13379 (2022) - 2021
- [j14]Meghna Lowalekar, Pradeep Varakantham, Patrick Jaillet:
Zone pAth Construction (ZAC) based Approaches for Effective Real-Time Ridesharing. J. Artif. Intell. Res. 70: 119-167 (2021) - [c108]Rajiv Ranjan Kumar, Pradeep Varakantham, Shih-Fen Cheng:
Adaptive Operating Hours for Improved Performance of Taxi Fleets. AAMAS 2021: 728-736 - [c107]Arpita Biswas, Gaurav Aggarwal, Pradeep Varakantham, Milind Tambe:
Learning Index Policies for Restless Bandits with Application to Maternal Healthcare. AAMAS 2021: 1467-1468 - [c106]Arpita Biswas, Gaurav Aggarwal, Pradeep Varakantham, Milind Tambe:
Learn to Intervene: An Adaptive Learning Policy for Restless Bandits in Application to Preventive Healthcare. IJCAI 2021: 4039-4046 - [c105]Dexun Li, Meghna Lowalekar, Pradeep Varakantham:
CLAIM: curriculum learning policy for influence maximization in unknown social networks. UAI 2021: 1455-1465 - [i18]Siddharth Nishtala, Lovish Madaan, Aditya Mate, Harshavardhan Kamarthi, Anirudh Grama, Divy Thakkar, Dhyanesh Narayanan, Suresh Chaudhary, Neha Madhiwalla, Ramesh Padmanabhan, Aparna Hegde, Pradeep Varakantham, Balaraman Ravindran, Milind Tambe:
Selective Intervention Planning using Restless Multi-Armed Bandits to Improve Maternal and Child Health Outcomes. CoRR abs/2103.09052 (2021) - [i17]Arpita Biswas, Gaurav Aggarwal, Pradeep Varakantham, Milind Tambe:
Learn to Intervene: An Adaptive Learning Policy for Restless Bandits in Application to Preventive Healthcare. CoRR abs/2105.07965 (2021) - [i16]Dexun Li, Meghna Lowalekar, Pradeep Varakantham:
CLAIM: Curriculum Learning Policy for Influence Maximization in Unknown Social Networks. CoRR abs/2107.03603 (2021) - [i15]Aditya Mate, Lovish Madaan, Aparna Taneja, Neha Madhiwalla, Shresth Verma, Gargi Singh, Aparna Hegde, Pradeep Varakantham, Milind Tambe:
Field Study in Deploying Restless Multi-Armed Bandits: Assisting Non-Profits in Improving Maternal and Child Health. CoRR abs/2109.08075 (2021) - [i14]Susobhan Ghosh, Pradeep Varakantham, Aniket Bhatkhande, Tamanna Ahmad, Anish Andheria, Wenjun Li, Aparna Taneja, Divy Thakkar, Milind Tambe:
Facilitating human-wildlife cohabitation through conflict prediction. CoRR abs/2109.10637 (2021) - [i13]Avinandan Bose, Pradeep Varakantham:
Conditional Expectation based Value Decomposition for Scalable On-Demand Ride Pooling. CoRR abs/2112.00579 (2021) - 2020
- [c104]Sanket Shah, Meghna Lowalekar, Pradeep Varakantham:
Neural Approximate Dynamic Programming for On-Demand Ride-Pooling. AAAI 2020: 507-515 - [c103]Sanket Shah, Arunesh Sinha, Pradeep Varakantham, Andrew Perrault, Milind Tambe:
Solving Online Threat Screening Games using Constrained Action Space Reinforcement Learning. AAAI 2020: 2226-2235 - [c102]Srishti Dhamija, Alolika Gon, Pradeep Varakantham, William Yeoh:
Online Traffic Signal Control through Sample-Based Constrained Optimization. ICAPS 2020: 366-374 - [c101]Meghna Lowalekar, Pradeep Varakantham, Patrick Jaillet:
Competitive Ratios for Online Multi-capacity Ridesharing. AAMAS 2020: 771-779 - [i12]Rajiv Ranjan Kumar, Pradeep Varakantham:
On Solving Cooperative MARL Problems with a Few Good Experiences. CoRR abs/2001.07993 (2020) - [i11]Tanvi Verma, Pradeep Varakantham:
Value Variance Minimization for Learning Approximate Equilibrium in Aggregation Systems. CoRR abs/2003.07088 (2020) - [i10]Meghna Lowalekar, Pradeep Varakantham, Patrick Jaillet:
Zone pAth Construction (ZAC) based Approaches for Effective Real-Time Ridesharing. CoRR abs/2009.06051 (2020) - [i9]Meghna Lowalekar, Pradeep Varakantham, Patrick Jaillet:
Competitive Ratios for Online Multi-capacity Ridesharing. CoRR abs/2009.07925 (2020)
2010 – 2019
- 2019
- [c100]Meghna Lowalekar, Pradeep Varakantham, Patrick Jaillet:
ZAC: A Zone Path Construction Approach for Effective Real-Time Ridesharing. ICAPS 2019: 528-538 - [c99]Abhinav Bhatia, Pradeep Varakantham, Akshat Kumar:
Resource Constrained Deep Reinforcement Learning. ICAPS 2019: 610-620 - [c98]Tanvi Verma, Pradeep Varakantham, Hoong Chuin Lau:
Entropy Based Independent Learning in Anonymous Multi-Agent Settings. ICAPS 2019: 655-663 - [c97]Chung-Kyun Han, Shih-Fen Cheng, Pradeep Varakantham:
A Homophily-Free Community Detection Framework for Trajectories with Delayed Responses. AAMAS 2019: 2003-2005 - [c96]Muralidhar Konda, Pradeep Varakantham, Aayush Saxena, Meghna Lowalekar:
RE-ORG: An Online Repositioning Guidance Agent. AAMAS 2019: 2369-2371 - [c95]Tanvi Verma, Pradeep Varakantham:
Correlated Learning for Aggregation Systems. UAI 2019: 60-70 - [i8]Sanket Shah, Arunesh Sinha, Pradeep Varakantham, Andrew Perrault, Milind Tambe:
Solving Online Threat Screening Games using Constrained Action Space Reinforcement Learning. CoRR abs/1911.08799 (2019) - [i7]Sanket Shah, Meghna Lowalekar, Pradeep Varakantham:
Neural Approximate Dynamic Programming for On-Demand Ride-Pooling. CoRR abs/1911.08842 (2019) - 2018
- [j13]Meghna Lowalekar, Pradeep Varakantham, Patrick Jaillet:
Online spatio-temporal matching in stochastic and dynamic domains. Artif. Intell. 261: 71-112 (2018) - [j12]Pradeep Varakantham, Akshat Kumar, Hoong Chuin Lau, William Yeoh:
Risk-Sensitive Stochastic Orienteering Problems for Trip Optimization in Urban Environments. ACM Trans. Intell. Syst. Technol. 9(3): 24:1-24:25 (2018) - [c94]Supriyo Ghosh, Pradeep Varakantham:
Dispatch Guided Allocation Optimization for Effective Emergency Response. AAAI 2018: 775-783 - [c93]Shashi Shekhar Jha, Shih-Fen Cheng, Meghna Lowalekar, Nicholas Wong, Rishikeshan Rajendram, Trong Khiem Tran, Pradeep Varakantham, Trong Nghia Truong, Firmansyah Bin Abd Rahman:
Upping the Game of Taxi Driving in the Age of Uber. AAAI 2018: 7779-7785 - [c92]Muralidhar Konda, Supriyo Ghosh, Pradeep Varakantham:
Reserved Optimisation: Handling Incident Priorities in Emergency Response Systems. ICAPS 2018: 330-338 - [c91]Pallavi Manohar, Pradeep Varakantham, Hoong Chuin Lau:
Bounded Rank Optimization for Effective and Efficient Emergency Response. ICAPS 2018: 375-382 - [c90]Shashi Shekhar Jha, Shih-Fen Cheng, Meghna Lowalekar, Nicholas Wong, Rishikeshan Rajendram, Pradeep Varakantham, Nghia Troung Troung, Firmansyah Bin Abd Rahman:
A Driver Guidance System for Taxis in Singapore. AAMAS 2018: 1820-1822 - [c89]Pritee Agrawal, Pradeep Varakantham, William Yeoh:
Decentralized Planning for Non-dedicated Agent Teams with Submodular Rewards in Uncertain Environments. UAI 2018: 958-967 - [i6]Tanvi Verma, Pradeep Varakantham, Hoong Chuin Lau:
Entropy Controlled Non-Stationarity for Improving Performance of Independent Learners in Anonymous MARL Settings. CoRR abs/1803.09928 (2018) - [i5]Abhinav Bhatia, Pradeep Varakantham, Akshat Kumar:
Resource Constrained Deep Reinforcement Learning. CoRR abs/1812.00600 (2018) - [i4]Srishti Dhamija, Pradeep Varakantham:
TuSeRACT: Turn-Sample-Based Real-Time Traffic Signal Control. CoRR abs/1812.05591 (2018) - 2017
- [j11]Pradeep Varakantham, Bo An, Bryan Low, Jie Zhang:
Artificial Intelligence Research in Singapore: Assisting the Development of a Smart Nation. AI Mag. 38(3): 102-105 (2017) - [j10]Supriyo Ghosh, Pradeep Varakantham, Yossiri Adulyasak, Patrick Jaillet:
Dynamic Repositioning to Reduce Lost Demand in Bike Sharing Systems. J. Artif. Intell. Res. 58: 387-430 (2017) - [j9]Asrar Ahmed, Pradeep Varakantham, Meghna Lowalekar, Yossiri Adulyasak, Patrick Jaillet:
Sampling Based Approaches for Minimizing Regret in Uncertain Markov Decision Processes (MDPs). J. Artif. Intell. Res. 59: 229-264 (2017) - [c88]Rajiv Ranjan Kumar, Pradeep Varakantham, Akshat Kumar:
Decentralized Planning in Stochastic Environments with Submodular Rewards. AAAI 2017: 3021-3028 - [c87]Meghna Lowalekar, Pradeep Varakantham, Supriyo Ghosh, Sanjay Dominik Jena, Patrick Jaillet:
Online Repositioning in Bike Sharing Systems. ICAPS 2017: 200-208 - [c86]Supriyo Ghosh, Pradeep Varakantham:
Incentivizing the Use of Bike Trailers for Dynamic Repositioning in Bike Sharing Systems. ICAPS 2017: 373-381 - [c85]Tanvi Verma, Pradeep Varakantham, Sarit Kraus, Hoong Chuin Lau:
Augmenting Decisions of Taxi Drivers through Reinforcement Learning for Improving Revenues. ICAPS 2017: 409-418 - [c84]Rajiv Ranjan Kumar, Pradeep Varakantham:
Exploiting Anonymity and Homogeneity in Factored Dec-MDPs through Precomputed Binomial Distributions. AAMAS 2017: 732-740 - [c83]Pritee Agrawal, Pradeep Varakantham:
Proactive and Reactive Coordination of Non-dedicated Agent Teams Operating in Uncertain Environments. IJCAI 2017: 28-34 - [c82]Pradeep Varakantham, Na Fu:
Mechanism Design for Strategic Project Scheduling. IJCAI 2017: 4433-4439 - 2016
- [c81]Ping Hou, William Yeoh, Pradeep Varakantham:
Solving Risk-Sensitive POMDPs With and Without Cost Observations. AAAI 2016: 3138-3144 - [c80]Pradeep Varakantham, Na Fu, Hoong Chuin Lau:
A Proactive Sampling Approach to Project Scheduling under Uncertainty. AAAI 2016: 3195-3201 - [c79]Meghna Lowalekar, Pradeep Varakantham, Patrick Jaillet:
Online Spatio-Temporal Matching in Stochastic and Dynamic Domains. AAAI 2016: 3271-3277 - [c78]Akshat Kumar, Arambam James Singh, Pradeep Varakantham, Daniel Sheldon:
Robust Decision Making for Stochastic Network Design. AAAI 2016: 3857-3863 - [c77]Soujanya Lanka, Deepika Pathania, Pooja Kushalappa, Pradeep Varakantham:
NLU Framework for Voice Enabling Non-Native Applications on Smart Devices. AAAI 2016: 4359-4360 - [c76]Na Fu, Pradeep Varakantham, Hoong Chuin Lau:
Robust Partial Order Schedules for RCPSP/max with Durational Uncertainty. ICAPS 2016: 124-130 - [c75]Supriyo Ghosh, Pradeep Varakantham:
Strategic Planning for Setting Up Base Stations in Emergency Medical Systems. ICAPS 2016: 385-393 - [c74]Meghna Lowalekar, Pradeep Varakantham, Akshat Kumar:
Robust Influence Maximization: (Extended Abstract). AAMAS 2016: 1395-1396 - [c73]Hoong Chuin Lau, Aldy Gunawan, Pradeep Varakantham, Wenjie Wang:
PRESS: PeRsonalized Event Scheduling recommender System (Demonstration). AAMAS 2016: 1513-1515 - [c72]Radhika Arava, Pradeep Varakantham:
Detecting Communities Using Coordination Games: A Short Paper. ECAI 2016: 1752-1753 - [c71]Aldy Gunawan, Hoong Chuin Lau, Pradeep Varakantham, Wenjie Wang:
An Intelligent System for Personalized Conference Event Recommendation and Scheduling. ECAI 2016: 1797-1802 - [c70]Pritee Agrawal, Pradeep Varakantham, William Yeoh:
Scalable Greedy Algorithms for Task/Resource Constrained Multi-Agent Stochastic Planning. IJCAI 2016: 10-16 - [c69]Supriyo Ghosh, Michael A. Trick, Pradeep Varakantham:
Robust Repositioning to Counter Unpredictable Demand in Bike Sharing Systems. IJCAI 2016: 3096-3102 - [c68]Pradeep Varakantham:
Sequential Decision Making for Improving Efficiency in Urban Environments. IJCAI 2016: 4090-4093 - 2015
- [j8]Eric Shieh, Albert Xin Jiang, Amulya Yadav, Pradeep Varakantham, Milind Tambe:
An extended study on addressing defender teamwork while accounting for uncertainty in attacker defender games using iterative Dec-MDPs. Multiagent Grid Syst. 11(4): 189-226 (2015) - [j7]Na Fu, Hoong Chuin Lau, Pradeep Varakantham:
Robust execution strategies for project scheduling with unreliable resources and stochastic durations. J. Sched. 18(6): 607-622 (2015) - [c67]Sandhya Saisubramanian, Pradeep Varakantham, Hoong Chuin Lau:
Risk Based Optimization for Improving Emergency Medical Systems. AAAI 2015: 702-708 - [c66]Yossiri Adulyasak, Pradeep Varakantham, Asrar Ahmed, Patrick Jaillet:
Solving Uncertain MDPs with Objectives that Are Separable over Instantiations of Model Uncertainty. AAAI 2015: 3454-3460 - [c65]Supriyo Ghosh, Pradeep Varakantham, Yossiri Adulyasak, Patrick Jaillet:
Dynamic Redeployment to Counter Congestion or Starvation in Vehicle Sharing Systems. AAAI Workshop: AI for Cities 2015 - [c64]Supriyo Ghosh, Pradeep Varakantham, Yossiri Adulyasak, Patrick Jaillet:
Dynamic Redeployment to Counter Congestion or Starvation in Vehicle Sharing Systems. ICAPS 2015: 79-87 - [c63]Pradeep Varakantham, Hala Mostafa, Na Fu, Hoong Chuin Lau:
DIRECT: A Scalable Approach for Route Guidance in Selfish Orienteering Problems. AAMAS 2015: 483-491 - [c62]Pritee Agrawal, Akshat Kumar, Pradeep Varakantham:
Near-Optimal Decentralized Power Supply Restoration in Smart Grids. AAMAS 2015: 1275-1283 - [c61]Supriyo Ghosh, Akshat Kumar, Pradeep Varakantham:
Probabilistic Inference Based Message-Passing for Resource Constrained DCOPs. IJCAI 2015: 411-417 - [c60]Supriyo Ghosh, Pradeep Varakantham, Yossiri Adulyasak, Patrick Jaillet:
Dynamic Redeployment to Counter Congestion or Starvation in Vehicle Sharing Systems. SOCS 2015: 230-231 - [c59]William Yeoh, Pradeep Varakantham, Xiaoxun Sun, Sven Koenig:
Incremental DCOP Search Algorithms for Solving Dynamic DCOP Problems. WI-IAT (2) 2015: 257-264 - [c58]Jiali Du, Pradeep Varakantham, Akshat Kumar, Shih-Fen Cheng:
Learning and Controlling Network Diffusion in Dependent Cascade Models. WI-IAT (2) 2015: 336-343 - 2014
- [j6]Jun-young Kwak, Pradeep Varakantham, Rajiv T. Maheswaran, Yu-Han Chang, Milind Tambe, Burcin Becerik-Gerber, Wendy Wood:
TESLA: an extended study of an energy-saving agent that leverages schedule flexibility. Auton. Agents Multi Agent Syst. 28(4): 605-636 (2014) - [c57]Pradeep Varakantham, Yossiri Adulyasak, Patrick Jaillet:
Decentralized Stochastic Planning with Anonymity in Interactions. AAAI 2014: 2505-2512 - [c56]Matthew Brown, Sandhya Saisubramanian, Pradeep Varakantham, Milind Tambe:
STREETS: Game-Theoretic Traffic Patrolling with Exploration and Exploitation. AAAI 2014: 2966-2971 - [c55]Ping Hou, William Yeoh, Pradeep Varakantham:
Revisiting Risk-Sensitive MDPs: New Algorithms and Results. ICAPS 2014 - [c54]Jun-young Kwak, Debarun Kar, William B. Haskell, Pradeep Varakantham, Milind Tambe:
Building THINC: user incentivization and meeting rescheduling for energy savings. AAMAS 2014: 925-932 - [c53]Jiali Du, Akshat Kumar, Pradeep Varakantham:
On understanding diffusion dynamics of patrons at a theme park. AAMAS 2014: 1501-1502 - [c52]Eric Anyung Shieh, Albert Xin Jiang, Amulya Yadav, Pradeep Varakantham, Milind Tambe:
Unleashing Dec-MDPs in Security Games: Enabling Effective Defender Teamwork. ECAI 2014: 819-824 - [c51]Archie C. Chapman, Pradeep Varakantham:
Marginal Contribution Stochastic Games for Dynamic Resource Allocation. PRIMA 2014: 333-340 - [i3]Na Fu, Hoong Chuin Lau, Pradeep Varakantham, Fei Xiao:
Robust Local Search for Solving RCPSP/max with Durational Uncertainty. CoRR abs/1401.4595 (2014) - 2013
- [c50]Pradeep Varakantham, Na Fu, William Yeoh, Shih-Fen Cheng, Hoong Chuin Lau:
Budgeted Personalized Incentive Approaches for Smoothing Congestion in Resource Networks. ADT 2013: 375-386 - [c49]Pradeep Varakantham, Akshat Kumar:
Optimization Approaches for Solving Chance Constrained Stochastic Orienteering Problems. ADT 2013: 387-398 - [c48]Jun-young Kwak, Pradeep Varakantham, Rajiv T. Maheswaran, Yu-Han Chang, Milind Tambe, Burcin Becerik-Gerber, Wendy Wood:
TESLA: an energy-saving agent that leverages schedule flexibility. AAMAS 2013: 965-972 - [c47]Pradeep Varakantham, Hoong Chuin Lau, Zhi Yuan:
Scalable Randomized Patrolling for Securing Rapid Transit Networks. IAAI 2013: 1563-1568 - [c46]Asrar Ahmed, Pradeep Varakantham, Yossiri Adulyasak, Patrick Jaillet:
Regret based Robust Solutions for Uncertain Markov Decision Processes. NIPS 2013: 881-889 - [c45]Shih-Fen Cheng, Larry Lin, Jiali Du, Hoong Chuin Lau, Pradeep Varakantham:
An agent-based simulation approach to experience management in theme parks. WSC 2013: 1527-1538 - 2012
- [j5]Sam Blisard, Ted Carmichael, Li Ding, Tim Finin, Wende Frost, Arthur C. Graesser, Mirsad Hadzikadic, Lalana Kagal, Geert-Jan M. Kruijff, Pat Langley, James C. Lester, Deborah L. McGuinness, Jack Mostow, Panagiotis Papadakis, Fiora Pirri, Rashmi Prasad, Svetlana Stoyanchev, Pradeep Varakantham:
Reports of the AAAI 2011 Fall Symposia. AI Mag. 33(1): 71-78 (2012) - [j4]Na Fu, Hoong Chuin Lau, Pradeep Varakantham, Fei Xiao:
Robust Local Search for Solving RCPSP/max with Durational Uncertainty. J. Artif. Intell. Res. 43: 43-86 (2012) - [c44]Pradeep Varakantham, Shih-Fen Cheng, Geoffrey J. Gordon, Asrar Ahmed:
Decision Support for Agent Populations in Uncertain and Congested Environments. AAAI 2012: 1471-1477 - [c43]Jun-young Kwak, Pradeep Varakantham, Rajiv T. Maheswaran, Milind Tambe, Farrokh Jazizadeh, Geoffrey Kavulya, Laura Klein, Burcin Becerik-Gerber, Timothy Hayes, Wendy Wood:
SAVES: a sustainable multiagent application to conserve building energy considering occupants. AAMAS 2012: 21-28 - [c42]Simon Andrew Williamson, Pradeep Varakantham, Ong Chen Hui, Debin Gao:
Active malware analysis using stochastic games. AAMAS 2012: 29-36 - [c41]Geoffrey J. Gordon, Pradeep Varakantham, William Yeoh, Hoong Chuin Lau, Ajay S. Aravamudhan, Shih-Fen Cheng:
Lagrangian relaxation for large-scale multi-agent planning. AAMAS 2012: 1227-1228 - [c40]Pradeep Varakantham, Janusz Marecki:
Delayed observation planning in partially observable domains. AAMAS 2012: 1235-1236 - [c39]Pradeep Varakantham, William Yeoh, Prasanna Velagapudi, Katia P. Sycara, Paul Scerri:
Prioritized shaping of models for solving DEC-POMDPs. AAMAS 2012: 1269-1270 - [c38]Jun-young Kwak, Pradeep Varakantham, Rajiv T. Maheswaran, Milind Tambe, Farrokh Jazizadeh, Geoffrey Kavulya, Laura Klein, Burcin Becerik-Gerber, Timothy Hayes, Wendy Wood:
Sustainable multiagent application to conserve energy (demonstration). AAMAS 2012: 1455-1456 - [c37]Geoffrey J. Gordon, Pradeep Varakantham, William Yeoh, Hoong Chuin Lau, Ajay S. Aravamudhan, Shih-Fen Cheng:
Lagrangian Relaxation for Large-Scale Multi-agent Planning. IAT 2012: 494-501 - [c36]Asrar Ahmed, Pradeep Varakantham, Shih-Fen Cheng:
Uncertain Congestion Games with Assorted Human Agent Populations. UAI 2012: 44-53 - [c35]Hoong Chuin Lau, William Yeoh, Pradeep Varakantham, Duc Thien Nguyen, HuaXing Chen:
Dynamic Stochastic Orienteering Problems for Risk-Aware Applications. UAI 2012: 448-458 - [i2]Asrar Ahmed, Pradeep Varakantham, Shih-Fen Cheng:
Uncertain Congestion Games with Assorted Human Agent Populations. CoRR abs/1210.4848 (2012) - [i1]Hoong Chuin Lau, William Yeoh, Pradeep Varakantham, Duc Thien Nguyen, HuaXing Chen:
Dynamic Stochastic Orienteering Problems for Risk-Aware Applications. CoRR abs/1210.4874 (2012) - 2011
- [c34]Prasanna Velagapudi, Pradeep Varakantham, Katia P. Sycara, Paul Scerri:
Distributed model shaping for scaling to decentralized POMDPs with hundreds of agents. AAMAS 2011: 955-962 - [c33]William Yeoh, Pradeep Varakantham, Xiaoxun Sun, Sven Koenig:
Incremental DCOP search algorithms for solving dynamic DCOPs. AAMAS 2011: 1069-1070 - [c32]Pradeep Varakantham, Shih-Fen Cheng, Nguyen Thi Duon:
Decentralized decision support for an agent population in dynamic and uncertain domains. AAMAS 2011: 1147-1148 - [c31]Pradeep Varakantham, Nathan Schurr, Alan Carlin, Christopher Amato:
Adaptive decision support for structured organizations: a case for OrgPOMDPs. AAMAS 2011: 1149-1150 - [c30]Pradeep Varakantham, Nathan Schurr, Alan Carlin, Christopher Amato:
Decision Support in Organizations: A Case for OrgPOMDPs. IAT 2011: 163-170 - [c29]Pradeep Varakantham:
Social Model Shaping for Solving Generic DEC-POMDPs. IAT 2011: 180-187 - 2010
- [j3]Makoto Tasaki, Yuichi Yabu, Yuki Iwanari, Makoto Yokoo, Janusz Marecki, Pradeep Varakantham, Milind Tambe:
Introducing communication in Dis-POMDPs with locality of interaction. Web Intell. Agent Syst. 8(3): 303-311 (2010) - [c28]Na Fu, Pradeep Varakantham, Hoong Chuin Lau:
Towards Finding Robust Execution Strategies for RCPSP/max with Durational Uncertainty. ICAPS 2010: 73-80 - [c27]Janusz Marecki, Pradeep Varakantham:
Risk-sensitive planning in partially observable environments. AAMAS 2010: 1357-1368 - [c26]Praveen Paruchuri, Pradeep Varakantham, Katia P. Sycara, Paul Scerri:
Analyzing the impact of human bias on human-agent teams in resource allocation domains. AAMAS 2010: 1593-1594 - [c25]Praveen Paruchuri, Pradeep Varakantham, Katia P. Sycara, Paul Scerri:
Effect of Human Biases on Human-Agent Teams. IAT 2010: 327-334 - [c24]Janusz Marecki, Mudhakar Srivatsa, Pradeep Varakantham:
A Decision Theoretic Approach to Data Leakage Prevention. SocialCom/PASSAT 2010: 776-784
2000 – 2009
- 2009
- [c23]Pradeep Varakantham, Jun-young Kwak, Matthew E. Taylor, Janusz Marecki, Paul Scerri, Milind Tambe:
Exploiting Coordination Locales in Distributed POMDPs via Social Model Shaping. ICAPS 2009 - [c22]William Yeoh, Pradeep Varakantham, Sven Koenig:
Caching schemes for DCOP search algorithms. AAMAS (1) 2009: 609-616 - 2008
- [c21]Pradeep Varakantham, Stephen F. Smith:
Linear Relaxation Techniques for Task Management in Uncertain Settings. ICAPS 2008: 363-371 - [c20]Janusz Marecki, Tapana Gupta, Pradeep Varakantham, Milind Tambe, Makoto Yokoo:
Not all agents are equal: scaling up distributed POMDPs for agent networks. AAMAS (1) 2008: 485-492 - [c19]Makoto Tasaki, Yuichi Yabu, Yuki Iwanari, Makoto Yokoo, Milind Tambe, Janusz Marecki, Pradeep Varakantham:
Introducing Communication in Dis-POMDPs with Locality of Interaction. IAT 2008: 169-175 - 2007
- [c18]Pradeep Varakantham, Janusz Marecki, Milind Tambe, Makoto Yokoo:
SPIDER Attack on a Network of POMDPs: Towards Quality Bounded Solutions. AAAI Spring Symposium: Game Theoretic and Decision Theoretic Agents 2007: 68-75 - [c17]Pradeep Varakantham, Janusz Marecki, Yuichi Yabu, Milind Tambe, Makoto Yokoo:
Letting loose a SPIDER on a network of POMDPs: generating quality guaranteed policies. AAMAS 2007: 218 - [c16]Tapana Gupta, Pradeep Varakantham, Timothy W. Rauenbusch, Milind Tambe:
Demonstration of teamwork in uncertain domains using hybrid BDI-POMDP systems. AAMAS 2007: 264 - [c15]Pradeep Varakantham, Rajiv T. Maheswaran, Tapana Gupta, Milind Tambe:
Towards Efficient Computation of Error Bounded Solutions in POMDPs: Expected Value Approximation and Dynamic Disjunctive Beliefs. IJCAI 2007: 2638-2644 - 2006
- [j2]Rajiv T. Maheswaran, Jonathan P. Pearce, Emma Bowring, Pradeep Varakantham, Milind Tambe:
Privacy Loss in Distributed Constraint Reasoning: A Quantitative Framework for Analysis and its Applications. Auton. Agents Multi Agent Syst. 13(1): 27-60 (2006) - [c14]Milind Tambe, Emma Bowring, Jonathan P. Pearce, Pradeep Varakantham, David V. Pynadath, Paul Scerri:
Electric Elves: What Went Wrong and Why. AAAI Spring Symposium: What Went Wrong and Why: Lessons from AI Research and Applications 2006: 34-39 - [c13]Yoonheui Kim, Ranjit Nair, Pradeep Varakantham, Milind Tambe, Makoto Yokoo:
Exploiting Locality of Interaction in Networked Distributed POMDPs. AAAI Spring Symposium: Distributed Plan and Schedule Management 2006: 41-48 - [c12]Pradeep Varakantham, Ranjit Nair, Milind Tambe, Makoto Yokoo:
Winning back the CUP for distributed POMDPs: planning over continuous belief spaces. AAMAS 2006: 289-296 - [c11]Nathan Schurr, Pradeep Varakantham, Emma Bowring, Milind Tambe, Barbara J. Grosz:
Asimovian Multiagents: Applying Laws of Robotics to Teams of Humans and Agents. PROMAS 2006: 41-55 - 2005
- [c10]Ranjit Nair, Pradeep Varakantham, Milind Tambe, Makoto Yokoo:
Networked Distributed POMDPs: A Synthesis of Distributed Constraint Optimization and POMDPs. AAAI 2005: 133-139 - [c9]Rajiv T. Maheswaran, Jonathan P. Pearce, Pradeep Varakantham, Emma Bowring, Milind Tambe:
Valuations of Possible States (VPS): A Quantitative Framework for Analysis of Privacy Loss Among Collaborative Personal Assistant Agents. AAAI Spring Symposium: Persistent Assistants: Living and Working with AI 2005: 60-67 - [c8]Pradeep Varakantham, Rajiv T. Maheswaran, Milind Tambe:
Practical POMDPs for Personal Assistant Domains. AAAI Spring Symposium: Persistent Assistants: Living and Working with AI 2005: 68-75 - [c7]Milind Tambe, Emma Bowring, Hyuckchul Jung, Gal A. Kaminka, Rajiv T. Maheswaran, Janusz Marecki, Pragnesh Jay Modi, Ranjit Nair, Stephen Okamoto, Jonathan P. Pearce, Praveen Paruchuri, David V. Pynadath, Paul Scerri, Nathan Schurr, Pradeep Varakantham:
Conflicts in teamwork: hybrids to the rescue. AAMAS 2005: 3-10 - [c6]Pradeep Varakantham, Rajiv T. Maheswaran, Milind Tambe:
Exploiting belief bounds: practical POMDPs for personal assistant agents. AAMAS 2005: 978-985 - [c5]Rajiv T. Maheswaran, Jonathan P. Pearce, Pradeep Varakantham, Emma Bowring, Milind Tambe:
Valuations of Possible States (VPS): a quantitative framework for analysis of privacy loss among collaborative personal assistant agents. AAMAS 2005: 1030-1037 - [c4]Ranjit Nair, Pradeep Varakantham, Milind Tambe, Makoto Yokoo:
Networked Distributed POMDPs: A Synergy of Distributed Constraint Optimization and POMDPs. IJCAI 2005: 1758-1760 - [c3]Pradeep Varakantham, Rajiv T. Maheswaran, Milind Tambe:
Implementation Techniques for Solving POMDPs in Personal Assistant Agents. PROMAS 2005: 76-89 - 2004
- [c2]Rajiv T. Maheswaran, Milind Tambe, Emma Bowring, Jonathan P. Pearce, Pradeep Varakantham:
Taking DCOP to the Real World: Efficient Complete Solutions for Distributed Multi-Event Scheduling. AAMAS 2004: 310-317 - 2003
- [c1]Rajiv T. Maheswaran, Milind Tambe, Pradeep Varakantham, Karen L. Myers:
Adjustable Autonomy Challenges in Personal Assistant Agents: A Position Paper. Agents and Computational Autonomy 2003: 187-194 - 2002
- [j1]Pradeep Varakantham, Santosh Kumar Gangwani, Kamalakar Karlapalem:
On handling component and transaction failures in multi agent systems. SIGecom Exch. 3(1): 32-43 (2002)
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2025-01-24 18:08 CET by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
