most citedA Meta-Game Evaluation Framework for Deep Multiagent Reinforcement Learning

1 citations · 1 across the 2 of their papers we have counts for

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2 papers

cs.GT2025

Policy Abstraction and Nash Refinement in Tree-Exploiting PSRO

Christine Konicki, Mithun Chakraborty, Michael P. Wellman

Policy Space Response Oracles (PSRO) interleaves empirical game-theoretic analysis with deep reinforcement learning (DRL) to solve games too complex for traditional analytic method…

cs.MA2024★ 1 cited

A Meta-Game Evaluation Framework for Deep Multiagent Reinforcement Learning

Zun Li, Michael P. Wellman

Evaluating deep multiagent reinforcement learning (MARL) algorithms is complicated by stochasticity in training and sensitivity of agent performance to the behavior of other agents…