Matthew J. Hausknecht

53 papers A* 10A 3C 2Journal 28Unranked 10

Year	Rank	Type	Title / Venue / Authors
2023	A	`conf`	One-Shot Learning from a Demonstration with Hierarchical Latent Language. AAMAS Nathaniel Weir, Xingdi Yuan, Marc-Alexandre Côté, Matthew J. Hausknecht, Romain Laroche, Ida Momennejad, Harm van Seijen, Benjamin Van Durme
2022	J	`jnl`	Consistent Dropout for Policy Gradient Reinforcement Learning. CoRR Matthew J. Hausknecht, Nolan Wagener
2022	A*	`conf`	MoCapAct: A Multi-Task Dataset for Simulated Humanoid Control. NeurIPS Nolan Wagener, Andrey Kolobov, Felipe Vieira Frujeri, Ricky Loynd, Ching-An Cheng, Matthew J. Hausknecht
2022	J	`jnl`	MoCapAct: A Multi-Task Dataset for Simulated Humanoid Control. CoRR Nolan Wagener, Andrey Kolobov, Felipe Vieira Frujeri, Ricky Loynd, Ching-An Cheng, Matthew J. Hausknecht
2022	J	`jnl`	One-Shot Learning from a Demonstration with Hierarchical Latent Language. CoRR Nathaniel Weir, Xingdi Yuan, Marc-Alexandre Côté, Matthew J. Hausknecht, Romain Laroche, Ida Momennejad, Harm van Seijen, Benjamin Van Durme
2022	J	`jnl`	Towards Flexible Inference in Sequential Decision Problems via Bidirectional Transformers. CoRR Micah Carroll, Jessy Lin, Orr Paradise, Raluca Georgescu, Mingfei Sun, David Bignell, Stephanie Milani, Katja Hofmann, Matthew J. Hausknecht, Anca D. Dragan, Sam Devlin
2022	J	`jnl`	UniMASK: Unified Inference in Sequential Decision Problems. CoRR Micah Carroll, Orr Paradise, Jessy Lin, Raluca Georgescu, Mingfei Sun, David Bignell, Stephanie Milani, Katja Hofmann, Matthew J. Hausknecht, Anca D. Dragan, Sam Devlin
2022	A*	`conf`	Uni[MASK]: Unified Inference in Sequential Decision Problems. NeurIPS Micah Carroll, Orr Paradise, Jessy Lin, Raluca Georgescu, Mingfei Sun, David Bignell, Stephanie Milani, Katja Hofmann, Matthew J. Hausknecht, Anca D. Dragan, Sam Devlin
2021	A*	`conf`	ALFWorld: Aligning Text and Embodied Environments for Interactive Learning. ICLR Mohit Shridhar, Xingdi Yuan, Marc-Alexandre Côté, Yonatan Bisk, Adam Trischler, Matthew J. Hausknecht
2021	J	`jnl`	Measuring Sample Efficiency and Generalization in Reinforcement Learning Benchmarks: NeurIPS 2020 Procgen Benchmark. CoRR 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
2021	—	`conf`	Reading and Acting while Blindfolded: The Need for Semantics in Text Game Agents. NAACL-HLT Shunyu Yao, Karthik Narasimhan, Matthew J. Hausknecht
2021	J	`jnl`	Reading and Acting while Blindfolded: The Need for Semantics in Text Game Agents. CoRR Shunyu Yao, Karthik Narasimhan, Matthew J. Hausknecht
2020	J	`jnl`	ALFWorld: Aligning Text and Embodied Environments for Interactive Learning. CoRR Mohit Shridhar, Xingdi Yuan, Marc-Alexandre Côté, Yonatan Bisk, Adam Trischler, Matthew J. Hausknecht
2020	A*	`conf`	Graph Constrained Reinforcement Learning for Natural Language Action Spaces. ICLR Prithviraj Ammanabrolu, Matthew J. Hausknecht
2020	J	`jnl`	Graph Constrained Reinforcement Learning for Natural Language Action Spaces. CoRR Prithviraj Ammanabrolu, Matthew J. Hausknecht
2020	J	`jnl`	How to Avoid Being Eaten by a Grue: Structured Exploration Strategies for Textual Worlds. CoRR Prithviraj Ammanabrolu, Ethan Tien, Matthew J. Hausknecht, Mark O. Riedl
2020	A*	`conf`	Interactive Fiction Games: A Colossal Adventure. AAAI Matthew J. Hausknecht, Prithviraj Ammanabrolu, Marc-Alexandre Côté, Xingdi Yuan
2020	—	`conf`	Keep CALM and Explore: Language Models for Action Generation in Text-based Games. EMNLP (1) Shunyu Yao, Rohan Rao, Matthew J. Hausknecht, Karthik Narasimhan
2020	J	`jnl`	Keep CALM and Explore: Language Models for Action Generation in Text-based Games. CoRR Shunyu Yao, Rohan Rao, Matthew J. Hausknecht, Karthik Narasimhan
2020	A*	`conf`	Learning Calibratable Policies using Programmatic Style-Consistency. ICML Eric Zhan, Albert Tseng, Yisong Yue, Adith Swaminathan, Matthew J. Hausknecht
2020	—	`conf`	Measuring Sample Efficiency and Generalization in Reinforcement Learning Benchmarks: NeurIPS 2020 Procgen Benchmark. NeurIPS (Competition and Demos) 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
2020	A*	`conf`	Working Memory Graphs. ICML Ricky Loynd, Roland Fernandez, Asli Celikyilmaz, Adith Swaminathan, Matthew J. Hausknecht
2019	J	`jnl`	Interactive Fiction Games: A Colossal Adventure. CoRR Matthew J. Hausknecht, Prithviraj Ammanabrolu, Marc-Alexandre Côté, Xingdi Yuan
2019	J	`jnl`	Learning Calibratable Policies using Programmatic Style-Consistency. CoRR Eric Zhan, Albert Tseng, Yisong Yue, Adith Swaminathan, Matthew J. Hausknecht
2019	J	`jnl`	Multi-Preference Actor Critic. CoRR Ishan Durugkar, Matthew J. Hausknecht, Adith Swaminathan, Patrick MacAlpine
2019	J	`jnl`	NAIL: A General Interactive Fiction Agent. CoRR Matthew J. Hausknecht, Ricky Loynd, Greg Yang, Adith Swaminathan, Jason D. Williams
2019	—	`conf`	ScriptNet: Neural Static Analysis for Malicious JavaScript Detection. MILCOM Jack W. Stokes, Rakshit Agrawal, Geoff McDonald, Matthew J. Hausknecht
2019	J	`jnl`	ScriptNet: Neural Static Analysis for Malicious JavaScript Detection. CoRR Jack W. Stokes, Rakshit Agrawal, Geoff McDonald, Matthew J. Hausknecht
2019	J	`jnl`	Working Memory Graphs. CoRR Ricky Loynd, Roland Fernandez, Asli Celikyilmaz, Adith Swaminathan, Matthew J. Hausknecht
2018	J	`jnl`	Counting to Explore and Generalize in Text-based Games. CoRR Xingdi Yuan, Marc-Alexandre Côté, Alessandro Sordoni, Romain Laroche, Remi Tachet des Combes, Matthew J. Hausknecht, Adam Trischler
2018	—	`conf`	Leveraging Grammar and Reinforcement Learning for Neural Program Synthesis. ICLR (Poster) Rudy Bunel, Matthew J. Hausknecht, Jacob Devlin, Rishabh Singh, Pushmeet Kohli
2018	J	`jnl`	Leveraging Grammar and Reinforcement Learning for Neural Program Synthesis. CoRR Rudy Bunel, Matthew J. Hausknecht, Jacob Devlin, Rishabh Singh, Pushmeet Kohli
2018	A*	`conf`	Revisiting the Arcade Learning Environment: Evaluation Protocols and Open Problems for General Agents (Extended Abstract). IJCAI Marlos C. Machado, Marc G. Bellemare, Erik Talvitie, Joel Veness, Matthew J. Hausknecht, Michael Bowling
2018	J	`jnl`	Revisiting the Arcade Learning Environment: Evaluation Protocols and Open Problems for General Agents. J. Artif. Intell. Res. Marlos C. Machado, Marc G. Bellemare, Erik Talvitie, Joel Veness, Matthew J. Hausknecht, Michael Bowling
2018	—	`conf`	TextWorld: A Learning Environment for Text-Based Games. CGW@IJCAI 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
2018	J	`jnl`	TextWorld: A Learning Environment for Text-based Games. CoRR 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
2017	J	`jnl`	Machine Learning Capabilities of a Simulated Cerebellum. IEEE Trans. Neural Networks Learn. Syst. Matthew J. Hausknecht, Wen-Ke Li, Michael D. Mauk, Peter Stone
2017	—	`conf`	Neural Program Meta-Induction. NIPS Jacob Devlin, Rudy Bunel, Rishabh Singh, Matthew J. Hausknecht, Pushmeet Kohli
2017	J	`jnl`	Neural Program Meta-Induction. CoRR Jacob Devlin, Rudy Bunel, Rishabh Singh, Matthew J. Hausknecht, Pushmeet Kohli
2017	J	`jnl`	Revisiting the Arcade Learning Environment: Evaluation Protocols and Open Problems for General Agents. CoRR Marlos C. Machado, Marc G. Bellemare, Erik Talvitie, Joel Veness, Matthew J. Hausknecht, Michael Bowling
2016	A*	`conf`	Deep Reinforcement Learning in Parameterized Action Space. ICLR (Poster) Matthew J. Hausknecht, Peter Stone
2015	J	`jnl`	Beyond Short Snippets: Deep Networks for Video Classification. CoRR Joe Yue-Hei Ng, Matthew J. Hausknecht, Sudheendra Vijayanarasimhan, Oriol Vinyals, Rajat Monga, George Toderici
2015	A*	`conf`	Beyond short snippets: Deep networks for video classification. CVPR Joe Yue-Hei Ng, Matthew J. Hausknecht, Sudheendra Vijayanarasimhan, Oriol Vinyals, Rajat Monga, George Toderici
2015	—	`conf`	Deep Recurrent Q-Learning for Partially Observable MDPs. AAAI Fall Symposia Matthew J. Hausknecht, Peter Stone
2015	J	`jnl`	Deep Recurrent Q-Learning for Partially Observable MDPs. CoRR Matthew J. Hausknecht, Peter Stone
2015	—	`conf`	The Impact of Determinism on Learning Atari 2600 Games. AAAI Workshop: Learning for General Competency in Video Games Matthew J. Hausknecht, Peter Stone
2014	J	`jnl`	A Neuroevolution Approach to General Atari Game Playing. IEEE Trans. Comput. Intell. AI Games Matthew J. Hausknecht, Joel Lehman, Risto Miikkulainen, Peter Stone
2013	J	`jnl`	Using a million cell simulation of the cerebellum: Network scaling and task generality. Neural Networks Wen-Ke Li, Matthew J. Hausknecht, Peter Stone, Michael D. Mauk
2012	A	`conf`	HyperNEAT-GGP: a hyperNEAT-based atari general game player. GECCO Matthew J. Hausknecht, Piyush Khandelwal, Risto Miikkulainen, Peter Stone
2011	A	`conf`	Autonomous Intersection Management: Multi-intersection optimization. IROS Matthew J. Hausknecht, Tsz-Chiu Au, Peter Stone
2011	—	`conf`	Dynamic lane reversal in traffic management. ITSC Matthew J. Hausknecht, Tsz-Chiu Au, Peter Stone, David Fajardo, S. Travis Waller
2010	C	`conf`	Learning Powerful Kicks on the Aibo ERS-7: The Quest for a Striker. RoboCup Matthew J. Hausknecht, Peter Stone
2009	C	`conf`	Detecting Stepping-Stone Intruders with Long Connection Chains. IAS Wei Ding, Matthew J. Hausknecht, Shou-Hsuan Stephen Huang, Zach Riggle