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Using evolutionary game theory to understand scalability in task allocation
2022
Proceedings of the Genetic and Evolutionary Computation Conference Companion
Cooperation is an important challenge in multi-agent systems. Decentralised learning of cooperation is difficult because interactions between agents make the environment non-stationary, and the reward structure tempts agents to act selfishly. A centralised solution bypasses these challenges, but may scale poorly with system size. Understanding this trade-off is important, but systematic comparisons have been limited to tasks with fully aligned incentives. We introduce a new task for studying
doi:10.1145/3520304.3529073
fatcat:3dc24gsa3je2jldkuggrvltxya