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ORCIDMatthew J. Hausknecht
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2020 – today
- 2023
[c25]Nathaniel Weir, Xingdi Yuan, Marc-Alexandre Côté, Matthew J. Hausknecht, Romain Laroche, Ida Momennejad, Harm van Seijen, Benjamin Van Durme:
One-Shot Learning from a Demonstration with Hierarchical Latent Language. AAMAS 2023: 2388-2390- 2022
- [c24]Micah Carroll, Orr Paradise, Jessy Lin, Raluca Georgescu, Mingfei Sun, David Bignell, Stephanie Milani, Katja Hofmann, Matthew J. Hausknecht, Anca D. Dragan, Sam Devlin:
Uni[MASK]: Unified Inference in Sequential Decision Problems. NeurIPS 2022 - [c23]Nolan Wagener, Andrey Kolobov, Felipe Vieira Frujeri, Ricky Loynd, Ching-An Cheng, Matthew J. Hausknecht:
MoCapAct: A Multi-Task Dataset for Simulated Humanoid Control. NeurIPS 2022 - [i24]Matthew J. Hausknecht, Nolan Wagener:
Consistent Dropout for Policy Gradient Reinforcement Learning. CoRR abs/2202.11818 (2022) - [i23]Nathaniel Weir, Xingdi Yuan, Marc-Alexandre Côté, Matthew J. Hausknecht, Romain Laroche, Ida Momennejad, Harm van Seijen, Benjamin Van Durme:
One-Shot Learning from a Demonstration with Hierarchical Latent Language. CoRR abs/2203.04806 (2022) - [i22]Micah Carroll, Jessy Lin, Orr Paradise, Raluca Georgescu, Mingfei Sun, David Bignell, Stephanie Milani, Katja Hofmann, Matthew J. Hausknecht, Anca D. Dragan, Sam Devlin:
Towards Flexible Inference in Sequential Decision Problems via Bidirectional Transformers. CoRR abs/2204.13326 (2022) - [i21]Nolan Wagener, Andrey Kolobov, Felipe Vieira Frujeri, Ricky Loynd, Ching-An Cheng, Matthew J. Hausknecht:
MoCapAct: A Multi-Task Dataset for Simulated Humanoid Control. CoRR abs/2208.07363 (2022) - [i20]Micah Carroll, Orr Paradise, Jessy Lin, Raluca Georgescu, Mingfei Sun, David Bignell, Stephanie Milani
, Katja Hofmann, Matthew J. Hausknecht, Anca D. Dragan, Sam Devlin:
UniMASK: Unified Inference in Sequential Decision Problems. CoRR abs/2211.10869 (2022) - 2021
- [c22]Mohit Shridhar, Xingdi Yuan, Marc-Alexandre Côté, Yonatan Bisk, Adam Trischler, Matthew J. Hausknecht:
ALFWorld: Aligning Text and Embodied Environments for Interactive Learning. ICLR 2021 - [c21]Shunyu Yao, Karthik Narasimhan, Matthew J. Hausknecht:
Reading and Acting while Blindfolded: The Need for Semantics in Text Game Agents. NAACL-HLT 2021: 3097-3102 - [i19]Shunyu Yao, Karthik Narasimhan, Matthew J. Hausknecht:
Reading and Acting while Blindfolded: The Need for Semantics in Text Game Agents. CoRR abs/2103.13552 (2021) - [i18]Sharada P. Mohanty, Jyotish Poonganam, Adrien Gaidon, Andrey Kolobov, Blake Wulfe, Dipam Chakraborty, Grazvydas Semetulskis, João Schapke, Jonas Kubilius, Jurgis Pasukonis, Linas Klimas, Matthew J. Hausknecht, Patrick MacAlpine, Quang Nhat Tran, Thomas Tumiel, Xiaocheng Tang, Xinwei Chen, Christopher Hesse, Jacob Hilton, William Hebgen Guss, Sahika Genc, John Schulman, Karl Cobbe:
Measuring Sample Efficiency and Generalization in Reinforcement Learning Benchmarks: NeurIPS 2020 Procgen Benchmark. CoRR abs/2103.15332 (2021) - 2020
- [c20]Matthew J. Hausknecht, Prithviraj Ammanabrolu, Marc-Alexandre Côté, Xingdi Yuan:
Interactive Fiction Games: A Colossal Adventure. AAAI 2020: 7903-7910 - [c19]Shunyu Yao, Rohan Rao, Matthew J. Hausknecht, Karthik Narasimhan:
Keep CALM and Explore: Language Models for Action Generation in Text-based Games. EMNLP (1) 2020: 8736-8754 - [c18]Prithviraj Ammanabrolu, Matthew J. Hausknecht:
Graph Constrained Reinforcement Learning for Natural Language Action Spaces. ICLR 2020 - [c17]Ricky Loynd, Roland Fernandez, Asli Celikyilmaz, Adith Swaminathan, Matthew J. Hausknecht:
Working Memory Graphs. ICML 2020: 6404-6414 - [c16]Eric Zhan, Albert Tseng, Yisong Yue, Adith Swaminathan, Matthew J. Hausknecht:
Learning Calibratable Policies using Programmatic Style-Consistency. ICML 2020: 11001-11011 - [c15]Sharada P. Mohanty, Jyotish Poonganam, Adrien Gaidon, Andrey Kolobov, Blake Wulfe, Dipam Chakraborty, Grazvydas Semetulskis, João Schapke, Jonas Kubilius, Jurgis Pasukonis, Linas Klimas, Matthew J. Hausknecht, Patrick MacAlpine, Quang Nhat Tran, Thomas Tumiel, Xiaocheng Tang, Xinwei Chen, Christopher Hesse, Jacob Hilton, William Hebgen Guss, Sahika Genc, John Schulman, Karl Cobbe:
Measuring Sample Efficiency and Generalization in Reinforcement Learning Benchmarks: NeurIPS 2020 Procgen Benchmark. NeurIPS (Competition and Demos) 2020: 361-395 - [i17]Prithviraj Ammanabrolu, Matthew J. Hausknecht:
Graph Constrained Reinforcement Learning for Natural Language Action Spaces. CoRR abs/2001.08837 (2020) - [i16]Prithviraj Ammanabrolu, Ethan Tien, Matthew J. Hausknecht, Mark O. Riedl:
How to Avoid Being Eaten by a Grue: Structured Exploration Strategies for Textual Worlds. CoRR abs/2006.07409 (2020) - [i15]Shunyu Yao, Rohan Rao, Matthew J. Hausknecht, Karthik Narasimhan:
Keep CALM and Explore: Language Models for Action Generation in Text-based Games. CoRR abs/2010.02903 (2020) - [i14]Mohit Shridhar, Xingdi Yuan, Marc-Alexandre Côté, Yonatan Bisk, Adam Trischler, Matthew J. Hausknecht:
ALFWorld: Aligning Text and Embodied Environments for Interactive Learning. CoRR abs/2010.03768 (2020)
2010 – 2019
- 2019
- [c14]Jack W. Stokes, Rakshit Agrawal, Geoff McDonald, Matthew J. Hausknecht:
ScriptNet: Neural Static Analysis for Malicious JavaScript Detection. MILCOM 2019: 1-8 - [i13]Matthew J. Hausknecht, Ricky Loynd, Greg Yang, Adith Swaminathan, Jason D. Williams:
NAIL: A General Interactive Fiction Agent. CoRR abs/1902.04259 (2019) - [i12]Jack W. Stokes, Rakshit Agrawal, Geoff McDonald, Matthew J. Hausknecht:
ScriptNet: Neural Static Analysis for Malicious JavaScript Detection. CoRR abs/1904.01126 (2019) - [i11]Ishan Durugkar, Matthew J. Hausknecht, Adith Swaminathan, Patrick MacAlpine:
Multi-Preference Actor Critic. CoRR abs/1904.03295 (2019) - [i10]Matthew J. Hausknecht, Prithviraj Ammanabrolu, Marc-Alexandre Côté, Xingdi Yuan:
Interactive Fiction Games: A Colossal Adventure. CoRR abs/1909.05398 (2019) - [i9]Eric Zhan, Albert Tseng, Yisong Yue, Adith Swaminathan, Matthew J. Hausknecht:
Learning Calibratable Policies using Programmatic Style-Consistency. CoRR abs/1910.01179 (2019) - [i8]Ricky Loynd, Roland Fernandez, Asli Celikyilmaz, Adith Swaminathan, Matthew J. Hausknecht:
Working Memory Graphs. CoRR abs/1911.07141 (2019) - 2018
- [j4]Marlos C. Machado, Marc G. Bellemare, Erik Talvitie, Joel Veness, Matthew J. Hausknecht, Michael Bowling:
Revisiting the Arcade Learning Environment: Evaluation Protocols and Open Problems for General Agents. J. Artif. Intell. Res. 61: 523-562 (2018) - [c13]Rudy Bunel, Matthew J. Hausknecht, Jacob Devlin, Rishabh Singh, Pushmeet Kohli:
Leveraging Grammar and Reinforcement Learning for Neural Program Synthesis. ICLR (Poster) 2018 - [c12]Marc-Alexandre Côté, Ákos Kádár, Xingdi Yuan, Ben Kybartas, Tavian Barnes, Emery Fine, James Moore, Matthew J. Hausknecht, Layla El Asri, Mahmoud Adada, Wendy Tay, Adam Trischler:
TextWorld: A Learning Environment for Text-Based Games. CGW@IJCAI 2018: 41-75 - [c11]Marlos C. Machado, Marc G. Bellemare, Erik Talvitie, Joel Veness, Matthew J. Hausknecht, Michael Bowling:
Revisiting the Arcade Learning Environment: Evaluation Protocols and Open Problems for General Agents (Extended Abstract). IJCAI 2018: 5573-5577 - [i7]Rudy Bunel, Matthew J. Hausknecht, Jacob Devlin, Rishabh Singh, Pushmeet Kohli:
Leveraging Grammar and Reinforcement Learning for Neural Program Synthesis. CoRR abs/1805.04276 (2018) - [i6]Xingdi Yuan, Marc-Alexandre Côté, Alessandro Sordoni, Romain Laroche, Remi Tachet des Combes, Matthew J. Hausknecht, Adam Trischler:
Counting to Explore and Generalize in Text-based Games. CoRR abs/1806.11525 (2018) - [i5]Marc-Alexandre Côté, Ákos Kádár, Xingdi Yuan, Ben Kybartas, Tavian Barnes, Emery Fine, James Moore, Matthew J. Hausknecht, Layla El Asri, Mahmoud Adada, Wendy Tay, Adam Trischler:
TextWorld: A Learning Environment for Text-based Games. CoRR abs/1806.11532 (2018) - 2017
- [j3]Matthew J. Hausknecht, Wen-Ke Li, Michael D. Mauk, Peter Stone:
Machine Learning Capabilities of a Simulated Cerebellum. IEEE Trans. Neural Networks Learn. Syst. 28(3): 510-522 (2017) - [c10]Jacob Devlin, Rudy Bunel, Rishabh Singh, Matthew J. Hausknecht, Pushmeet Kohli:
Neural Program Meta-Induction. NIPS 2017: 2080-2088 - [i4]Marlos C. Machado, Marc G. Bellemare, Erik Talvitie, Joel Veness, Matthew J. Hausknecht, Michael Bowling:
Revisiting the Arcade Learning Environment: Evaluation Protocols and Open Problems for General Agents. CoRR abs/1709.06009 (2017) - [i3]Jacob Devlin, Rudy Bunel, Rishabh Singh, Matthew J. Hausknecht, Pushmeet Kohli:
Neural Program Meta-Induction. CoRR abs/1710.04157 (2017) - 2016
- [c9]Matthew J. Hausknecht, Peter Stone:
Deep Reinforcement Learning in Parameterized Action Space. ICLR (Poster) 2016 - 2015
- [c8]Matthew J. Hausknecht, Peter Stone:
The Impact of Determinism on Learning Atari 2600 Games. AAAI Workshop: Learning for General Competency in Video Games 2015 - [c7]Matthew J. Hausknecht, Peter Stone:
Deep Recurrent Q-Learning for Partially Observable MDPs. AAAI Fall Symposia 2015: 29-37 - [c6]Joe Yue-Hei Ng, Matthew J. Hausknecht, Sudheendra Vijayanarasimhan, Oriol Vinyals, Rajat Monga, George Toderici:
Beyond short snippets: Deep networks for video classification. CVPR 2015: 4694-4702 - [i2]Joe Yue-Hei Ng, Matthew J. Hausknecht, Sudheendra Vijayanarasimhan, Oriol Vinyals, Rajat Monga, George Toderici:
Beyond Short Snippets: Deep Networks for Video Classification. CoRR abs/1503.08909 (2015) - [i1]Matthew J. Hausknecht, Peter Stone:
Deep Recurrent Q-Learning for Partially Observable MDPs. CoRR abs/1507.06527 (2015) - 2014
- [j2]Matthew J. Hausknecht, Joel Lehman, Risto Miikkulainen, Peter Stone:
A Neuroevolution Approach to General Atari Game Playing. IEEE Trans. Comput. Intell. AI Games 6(4): 355-366 (2014) - 2013
- [j1]Wen-Ke Li, Matthew J. Hausknecht, Peter Stone, Michael D. Mauk:
Using a million cell simulation of the cerebellum: Network scaling and task generality. Neural Networks 47: 95-102 (2013) - 2012
- [c5]Matthew J. Hausknecht, Piyush Khandelwal, Risto Miikkulainen, Peter Stone:
HyperNEAT-GGP: a hyperNEAT-based atari general game player. GECCO 2012: 217-224 - 2011
- [c4]Matthew J. Hausknecht, Tsz-Chiu Au, Peter Stone:
Autonomous Intersection Management: Multi-intersection optimization. IROS 2011: 4581-4586 - [c3]Matthew J. Hausknecht, Tsz-Chiu Au, Peter Stone, David Fajardo, S. Travis Waller:
Dynamic lane reversal in traffic management. ITSC 2011: 1929-1934 - 2010
- [c2]Matthew J. Hausknecht, Peter Stone:
Learning Powerful Kicks on the Aibo ERS-7: The Quest for a Striker. RoboCup 2010: 254-265
2000 – 2009
- 2009
- [c1]Wei Ding, Matthew J. Hausknecht, Shou-Hsuan Stephen Huang, Zach Riggle:
Detecting Stepping-Stone Intruders with Long Connection Chains. IAS 2009: 665-669
Coauthor Index
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