An evolved agent performing efficient path integration based homing and search

Authors:
R. J. Vickerstaff;E. A. Di Paolo
Affiliations:
Centre for Computational Neuroscience and Robotics, University of Sussex, Brighton, United Kingdom;Centre for Computational Neuroscience and Robotics, University of Sussex, Brighton, United Kingdom
Venue:
ECAL'05 Proceedings of the 8th European conference on Advances in Artificial Life
Year:
2005

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Abstract

This paper presents analysis and follow up experiments based on previous work where a neurally controlled simulated agent was evolved to navigate using path integration (PI). Specifically, we focus on one agent, the best one produced, and investigate two interesting features. Firstly, the agent stores its current coordinates in two leaky integrators, whose leakage is partially compensated for by a normalisation mechanism. We use a comparison between four network topologies to test if this normalised leakage mechanism is adaptive for the agent. Secondly, the controller generates efficient searching behaviour in the vicinity of its final goal. We begin an analysis of the dynamical system (DS) responsible for this, starting from a simple three variable system.