LEARNING MACHINE LEARNING INCENTIVES BY GRADIENT DESCENT FOR AGENT COOPERATION IN A DISTRIBUTED MULTI-AGENT SYSTEM

摘要

Machine learning techniques for multi-agent systems in which agents interact whilst performing their respective tasks. The techniques enable agents to learn to cooperate with one another, in particular by mixing incentives, in a way that improves their collective efficiency.