FairTest: Search-Based Fairness Testing for Multi-Agent Reinforcement Learning Systems
FairTest is proposed, a search-based testing approach that seeks the unfair executions of a MARL policy and combines search guidance with test prioritization, which detects the most fairness failures compared to three baselines with statistical significance and large effect sizes.
Xiao-Tong Wang, Xuan Xie
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