Yaqing Hou

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In this paper, we present a multi-agent reinforcement learning (MARL) framework that leverages the emergent behaviors from swarm intelligence (SI). The essential backbone of our framework is an flocking-regulated cooperative learning paradigm in which the cooperation among learning agents is realized via the self-organizing principles derived from natural(More)
Memetic Multi-Agent System (MeMAS) has recently emerged as a combination of memetic automaton and multi-agent system (MAS), wherein all meme-inspired agents acquire increasing learning capacity and intelligence through meme evolution. This paper further presents a study of MeMAS in developing human-like non-player characters in complex first-person shooter(More)
Memetic Multi-Agent System (MeMAS) emerges as an enhanced version of multi-agent systems with the implementation of meme-inspired agents. Previous research of MeMAS has developed a computational framework in which a series of memetic operations have been designed for implementing multiple interacting agents. This paper further endeavors to address the(More)
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