Revisiting the Arcade Learning Environment: Evaluation Protocols and Open Problems for General Agents (Extended Abstract)
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Marlos C. Machado | Marc G. Bellemare | Erik Talvitie | Joel Veness | Matthew J. Hausknecht | Michael H. Bowling | Michael Bowling | J. Veness | Erik Talvitie
[1] Shane Legg,et al. Human-level control through deep reinforcement learning , 2015, Nature.
[2] John Schulman,et al. Gotta Learn Fast: A New Benchmark for Generalization in RL , 2018, ArXiv.
[3] Marlos C. Machado,et al. Revisiting the Arcade Learning Environment: Evaluation Protocols and Open Problems for General Agents , 2017, J. Artif. Intell. Res..
[4] Mark B. Ring. CHILD: A First Step Towards Continual Learning , 1997, Machine Learning.
[5] Tom Schaul,et al. Prioritized Experience Replay , 2015, ICLR.
[6] Marlos C. Machado,et al. State of the Art Control of Atari Games Using Shallow Reinforcement Learning , 2015, AAMAS.
[7] Graham Kendall,et al. Editorial: IEEE Transactions on Computational Intelligence and AI in Games , 2015, IEEE Trans. Comput. Intell. AI Games.
[8] Andrew Zisserman,et al. Advances in Neural Information Processing Systems (NIPS) , 2007 .
[9] Peter Stone,et al. The Impact of Determinism on Learning Atari 2600 Games , 2015, AAAI Workshop: Learning for General Competency in Video Games.
[10] Marc G. Bellemare,et al. The Arcade Learning Environment: An Evaluation Platform for General Agents (Extended Abstract) , 2012, IJCAI.
[11] Marc G. Bellemare,et al. Investigating Contingency Awareness Using Atari 2600 Games , 2012, AAAI.