Neuroevolution of Cooperation in a Multi-Agent Foraging Task
thesisposted on 2022-09-06, 08:09 authored by Mostafa Khaled Mohamed Youssri Rizk
Teams of Artificially Intelligent agents can more effectively achieve their goals by learning to cooperate. Methods for learning cooperation can be centralised or decentralised but the trade-offs of applying these methods are not well understood. This thesis conducts an in-depth analysis of different learning methods. It introduces a new multi-agent task that facilitates the study of complex cooperation and implements it as part of a reusable experimental platform. It uses the platform to conduct a systematic comparison of centralised and decentralised learning, providing new insights into their trade-offs, and presents a theoretical model that generalises the findings to new contexts.