AI RESEARCH
TABX: A High-Throughput Sandbox Battle Simulator for Multi-Agent Reinforcement Learning
arXiv CS.AI
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ArXi:2602.01665v2 Announce Type: replace-cross The design of environments plays a critical role in shaping the development and evaluation of cooperative multi-agent reinforcement learning (MARL) algorithms. While existing benchmarks highlight critical challenges, they often lack the modularity required to design custom evaluation scenarios. We