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Shuze Chen

2 accepted papers

2025

Multi-agent Markov Entanglement

NeurIPS 2025spotlight

Value decomposition has long been a fundamental technique in multi-agent reinforcement learning and dynamic programming. Specifically, the value function of a global state $(s_1,s_2,\ldots,s_N)$ is often approximated as the sum of local functions: $V(s_1,s_2,\ldots,s_N)\approx\sum_{i=1}^N V_i(s_i)$.…

Cited by 0SourceScholar
2025

Towards Provably Efficient Learning of Imperfect Information Extensive-Form Games with Linear Function Approximation

UAI 2025

Despite significant advances in learning imperfect information extensive-form games (IIEFGs), most existing theoretical guarantees are limited to IIEFGs in the tabular case. To permit efficient learning of large-scale IIEFGs, we take the first step in studying two-player zero-sum IIEFGs with linear