Beyond short snippets: Deep networks for video classification J Yue-Hei Ng, M Hausknecht, S Vijayanarasimhan, O Vinyals, R Monga, ... Proceedings of the IEEE conference on computer vision and pattern …, 2015 | 3101 | 2015 |
Deep recurrent q-learning for partially observable mdps M Hausknecht, P Stone 2015 aaai fall symposium series, 2015 | 2284 | 2015 |
Revisiting the arcade learning environment: Evaluation protocols and open problems for general agents MC Machado, MG Bellemare, E Talvitie, J Veness, M Hausknecht, ... Journal of Artificial Intelligence Research 61, 523-562, 2018 | 653 | 2018 |
Deep reinforcement learning in parameterized action space M Hausknecht, P Stone arXiv preprint arXiv:1511.04143, 2015 | 404 | 2015 |
Textworld: A learning environment for text-based games MA Côté, A Kádár, X Yuan, B Kybartas, T Barnes, E Fine, J Moore, ... Computer Games: 7th Workshop, CGW 2018, Held in Conjunction with the 27th …, 2019 | 319 | 2019 |
Alfworld: Aligning text and embodied environments for interactive learning M Shridhar, X Yuan, MA Côté, Y Bisk, A Trischler, M Hausknecht arXiv preprint arXiv:2010.03768, 2020 | 311 | 2020 |
A neuroevolution approach to general atari game playing M Hausknecht, J Lehman, R Miikkulainen, P Stone IEEE Transactions on Computational Intelligence and AI in Games 6 (4), 355-366, 2014 | 259 | 2014 |
Leveraging grammar and reinforcement learning for neural program synthesis R Bunel, M Hausknecht, J Devlin, R Singh, P Kohli arXiv preprint arXiv:1805.04276, 2018 | 243 | 2018 |
Autonomous intersection management: Multi-intersection optimization M Hausknecht, TC Au, P Stone 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2011 | 203 | 2011 |
Interactive fiction games: A colossal adventure M Hausknecht, P Ammanabrolu, MA Côté, X Yuan Proceedings of the AAAI Conference on Artificial Intelligence 34 (05), 7903-7910, 2020 | 189 | 2020 |
Cooperation and communication in multiagent deep reinforcement learning MJ Hausknecht | 180 | 2016 |
For want of a nail: How absences cause events. P Wolff, AK Barbey, M Hausknecht Journal of Experimental Psychology: General 139 (2), 191, 2010 | 125 | 2010 |
Keep calm and explore: Language models for action generation in text-based games S Yao, R Rao, M Hausknecht, K Narasimhan arXiv preprint arXiv:2010.02903, 2020 | 124 | 2020 |
Graph constrained reinforcement learning for natural language action spaces P Ammanabrolu, M Hausknecht arXiv preprint arXiv:2001.08837, 2020 | 120 | 2020 |
Dynamic lane reversal in traffic management M Hausknecht, TC Au, P Stone, D Fajardo, T Waller 2011 14th International IEEE Conference on Intelligent Transportation …, 2011 | 120 | 2011 |
Half field offense: An environment for multiagent learning and ad hoc teamwork M Hausknecht, P Mupparaju, S Subramanian, S Kalyanakrishnan, ... AAMAS Adaptive Learning Agents (ALA) Workshop 3, 2016 | 105 | 2016 |
Neural program meta-induction J Devlin, RR Bunel, R Singh, M Hausknecht, P Kohli Advances in Neural Information Processing Systems 30, 2017 | 91 | 2017 |
HyperNEAT-GGP: A HyperNEAT-based Atari general game player M Hausknecht, P Khandelwal, R Miikkulainen, P Stone Proceedings of the 14th annual conference on Genetic and evolutionary …, 2012 | 80 | 2012 |
Using a million cell simulation of the cerebellum: network scaling and task generality WK Li, MJ Hausknecht, P Stone, MD Mauk Neural networks 47, 95-102, 2013 | 73 | 2013 |
Counting to explore and generalize in text-based games X Yuan, MA Côté, A Sordoni, R Laroche, RT Combes, M Hausknecht, ... arXiv preprint arXiv:1806.11525, 2018 | 61 | 2018 |