Background readings
We are building on decades of work done by us and others. If you want to understand our work then we would recommend familiarizing yourself with the following prior work.
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The OaK architecture
Richard S. Sutton
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The Alberta plan for AI research
Richard S. Sutton, Michael Bowling, Patrick M. Pilarski
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The big world hypothesis and its ramifications for AI
Khurram Javed, Richard S. Sutton
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SwiftTD: A fast and robust algorithm for temporal difference learning
Khurram Javed, Arsalan Sharifnassab, Richard S. Sutton
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Step-size optimization for continual learning
Thomas Degris, Khurram Javed, Arsalan Sharifnassab, Yuxin Liu, Richard S. Sutton
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Reward-respecting subtasks for model-based reinforcement learning
Richard S. Sutton, Marlos C. Machado, G. Zacharias Holland, David Szepesvari, Finbarr Timbers, Brian Tanner, Adam White
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The quest for a common model of the intelligent decision maker
Richard S. Sutton
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Reward is enough
David Silver, Satinder Singh, Doina Precup, Richard S. Sutton
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Planning with expectation models
Yi Wan, Zaheer Abbas, Adam White, Martha White, Richard S. Sutton
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On the role of tracking in stationary environments
Richard S. Sutton, Anna Koop, David Silver
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Scalable real-time recurrent learning using columnar-constructive networks
Khurram Javed, Haseeb Shah, Richard S. Sutton, Martha White