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.
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Vickerstaff, R.J., Di Paolo, E.A. (2005). An Evolved Agent Performing Efficient Path Integration Based Homing and Search. In: Capcarrère, M.S., Freitas, A.A., Bentley, P.J., Johnson, C.G., Timmis, J. (eds) Advances in Artificial Life. ECAL 2005. Lecture Notes in Computer Science(), vol 3630. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11553090_23
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DOI: https://doi.org/10.1007/11553090_23
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28848-0
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