Matthew J. Hausknecht

Publication Activity (10 Years)

Years Active: 2009-2023
Publications (10 Years): 39

Top Topics

Reinforcement Learning

Partially Observable

Video Classification

Top Venues

Publications

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)
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 (2022)
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)
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 (2022)
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)
Matthew J. Hausknecht, Nolan Wagener
Consistent Dropout for Policy Gradient Reinforcement Learning. CoRR (2022)
Shunyu Yao, Karthik Narasimhan, Matthew J. Hausknecht
Reading and Acting while Blindfolded: The Need for Semantics in Text Game Agents. CoRR (2021)
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 (2021)
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)
Shunyu Yao, Karthik Narasimhan, Matthew J. Hausknecht
Reading and Acting while Blindfolded: The Need for Semantics in Text Game Agents. NAACL-HLT (2021)
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)
Shunyu Yao, Rohan Rao, Matthew J. Hausknecht, Karthik Narasimhan
Keep CALM and Explore: Language Models for Action Generation in Text-based Games. CoRR (2020)
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 (2020)
Ricky Loynd, Roland Fernandez, Asli Celikyilmaz, Adith Swaminathan, Matthew J. Hausknecht
Working Memory Graphs. ICML (2020)
Mohit Shridhar, Xingdi Yuan, Marc-Alexandre Côté, Yonatan Bisk, Adam Trischler, Matthew J. Hausknecht
ALFWorld: Aligning Text and Embodied Environments for Interactive Learning. CoRR (2020)
Eric Zhan, Albert Tseng, Yisong Yue, Adith Swaminathan, Matthew J. Hausknecht
Learning Calibratable Policies using Programmatic Style-Consistency. ICML (2020)
Matthew J. Hausknecht, Prithviraj Ammanabrolu, Marc-Alexandre Côté, Xingdi Yuan
Interactive Fiction Games: A Colossal Adventure. AAAI (2020)
Prithviraj Ammanabrolu, Matthew J. Hausknecht
Graph Constrained Reinforcement Learning for Natural Language Action Spaces. ICLR (2020)
Prithviraj Ammanabrolu, Matthew J. Hausknecht
Graph Constrained Reinforcement Learning for Natural Language Action Spaces. CoRR (2020)
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)
Ricky Loynd, Roland Fernandez, Asli Celikyilmaz, Adith Swaminathan, Matthew J. Hausknecht
Working Memory Graphs. CoRR (2019)
Eric Zhan, Albert Tseng, Yisong Yue, Adith Swaminathan, Matthew J. Hausknecht
Learning Calibratable Policies using Programmatic Style-Consistency. CoRR (2019)
Jack W. Stokes, Rakshit Agrawal, Geoff McDonald, Matthew J. Hausknecht
ScriptNet: Neural Static Analysis for Malicious JavaScript Detection. CoRR (2019)
Matthew J. Hausknecht, Ricky Loynd, Greg Yang, Adith Swaminathan, Jason D. Williams
NAIL: A General Interactive Fiction Agent. CoRR (2019)
Matthew J. Hausknecht, Prithviraj Ammanabrolu, Marc-Alexandre Côté, Xingdi Yuan
Interactive Fiction Games: A Colossal Adventure. CoRR (2019)
Jack W. Stokes, Rakshit Agrawal, Geoff McDonald, Matthew J. Hausknecht
ScriptNet: Neural Static Analysis for Malicious JavaScript Detection. MILCOM (2019)
Ishan Durugkar, Matthew J. Hausknecht, Adith Swaminathan, Patrick MacAlpine
Multi-Preference Actor Critic. CoRR (2019)
Rudy Bunel, Matthew J. Hausknecht, Jacob Devlin, Rishabh Singh, Pushmeet Kohli
Leveraging Grammar and Reinforcement Learning for Neural Program Synthesis. ICLR (Poster) (2018)
Rudy Bunel, Matthew J. Hausknecht, Jacob Devlin, Rishabh Singh, Pushmeet Kohli
Leveraging Grammar and Reinforcement Learning for Neural Program Synthesis. CoRR (2018)
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 (2018)
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 (2018)
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)
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)
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 (2018)
Jacob Devlin, Rudy Bunel, Rishabh Singh, Matthew J. Hausknecht, Pushmeet Kohli
Neural Program Meta-Induction. NIPS (2017)
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) (2017)
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 (2017)
Jacob Devlin, Rudy Bunel, Rishabh Singh, Matthew J. Hausknecht, Pushmeet Kohli
Neural Program Meta-Induction. CoRR (2017)
Matthew J. Hausknecht, Peter Stone
Deep Reinforcement Learning in Parameterized Action Space. ICLR (Poster) (2016)
Matthew J. Hausknecht, Peter Stone
Deep Recurrent Q-Learning for Partially Observable MDPs. AAAI Fall Symposia (2015)
Matthew J. Hausknecht, Peter Stone
The Impact of Determinism on Learning Atari 2600 Games. AAAI Workshop: Learning for General Competency in Video Games (2015)
Matthew J. Hausknecht, Peter Stone
Deep Recurrent Q-Learning for Partially Observable MDPs. CoRR (2015)
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)
Joe Yue-Hei Ng, Matthew J. Hausknecht, Sudheendra Vijayanarasimhan, Oriol Vinyals, Rajat Monga, George Toderici
Beyond Short Snippets: Deep Networks for Video Classification. CoRR (2015)
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) (2014)
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 (2013)
Matthew J. Hausknecht, Piyush Khandelwal, Risto Miikkulainen, Peter Stone
HyperNEAT-GGP: a hyperNEAT-based atari general game player. GECCO (2012)
Matthew J. Hausknecht, Tsz-Chiu Au, Peter Stone
Autonomous Intersection Management: Multi-intersection optimization. IROS (2011)
Matthew J. Hausknecht, Tsz-Chiu Au, Peter Stone, David Fajardo, S. Travis Waller
Dynamic lane reversal in traffic management. ITSC (2011)
Matthew J. Hausknecht, Peter Stone
Learning Powerful Kicks on the Aibo ERS-7: The Quest for a Striker. RoboCup (2010)
Wei Ding, Matthew J. Hausknecht, Shou-Hsuan Stephen Huang, Zach Riggle
Detecting Stepping-Stone Intruders with Long Connection Chains. IAS (2009)