Kevin A. Wang — accepted AI-conference papers

2024

The Update-Equivalence Framework for Decision-Time Planning

Samuel Sokota, Gabriele Farina, David J Wu, Hengyuan Hu, Kevin A. Wang, J Zico Kolter +1

ICLR 2024poster

The process of revising (or constructing) a policy at execution time---known as decision-time planning---has been key to achieving superhuman performance in perfect-information games like chess and Go. A recent line of work has extended decision-time planning to imperfect-information games, leading…

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2024

Toward Optimal Policy Population Growth in Two-Player Zero-Sum Games

Stephen Marcus McAleer, JB Lanier, Kevin A. Wang, Pierre Baldi, Tuomas Sandholm, Roy Fox

ICLR 2024poster

In competitive two-agent environments, deep reinforcement learning (RL) methods like Policy Space Response Oracles (PSRO) often increase exploitability between iterations, which is problematic when training in large games. To address this issue, we introduce anytime double oracle (ADO), an algorithm…

Cited by 1 Source ↗PDF ↗Scholar ↗