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The Role of Working Memory in an Urban Pursuit Scenario

Most self-organizing models of moving agent collectives (simulated herds, bird flocks, etc.) employ reflexive agents that lack significant memory of past movements and previously encountered environmental features. Further, these agent collectives often act in fairly open environments where obstacles to movement are relatively sparse. In this work, we explore the hypothesis that a limited working memory of recently encountered environmental features, distributed throughout the collective, can improve task performance for a team of interacting agents that are operating in a highly occluded environment. Investigating a team of agents pursuing a mobile target in an “urban environment”, we found that the team benefited from 1) communication that coordinated team movements, and 2) from a working memory of the environment that was distributed among the agents, despite individual agents knowing only a small part of the relevant information. These results further our understanding of methodologies that can be applied to control robotic teams and swarm optimization, and may also provide insight into herd behavior of biological populations in some densely occluded environments.