CTC: The Composite Task Challenge for Cooperative Multi-Agent Reinforcement Learning
Researchers introduce the Composite Tasks Challenge (CTC), a new benchmark suite specifically designed to test both division of labor and cooperation in multi-agent reinforcement learning (MARL). Experiments show that nine leading MARL methods fail to solve any CTC tasks, achieving zero test winning rates. A guiding solution demonstrates that the tasks are solvable but remains suboptimal, emphasizing the benchmark's difficulty.
Why it matters: CTC exposes a significant gap in current cooperative MARL capabilities, providing a challenging benchmark to drive advances in division of labor and cooperation mechanisms.
Full story at: arXiv Multiagent Systems ↗