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GACA redefines multi-robot task allocation by optimizing group-level bidding, achieving nearly perfect allocation efficiency in decentralized systems.
Reinforcement learning can teach robot swarms to bid more effectively in task allocation auctions, outperforming hand-crafted heuristics without sacrificing decentralized control.