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cs.AI2026

Benchmarking the Limits of In-Context Reinforcement Learning for Ad-Hoc Teamwork

Yuheng Jing, Kai Li, Ziwen Zhang +8

In-Context Reinforcement Learning (ICRL) has enabled foundation agents to adapt instantaneously to novel tasks, yet its efficacy in Ad-Hoc Teamwork (AHT)-where coordination with un…