title: Goal-oriented robot navigation learning using a multi-scale space representation.
abstract: There has been extensive research in recent years on the multi-scale nature of hippocampal place cells and entorhinal grid cells encoding which led to many speculations on their role in spatial cognition. In this paper we focus on the multi-scale nature of place cells and how they contribute to faster learning during goal-oriented navigation when compared to a spatial cognition system composed of single scale place cells. The task consists of a circular arena with a fixed goal location, in which a robot is trained to find the shortest path to the goal after a number of learning trials. Synaptic connections are modified using a reinforcement learning paradigm adapted to the place cells multi-scale architecture. The model is evaluated in both simulation and physical robots. We find that larger scale and combined multi-scale representations favor goal-oriented navigation task learning.
authors.affiliation: University of South Florida, United States; Universidad de la Republica, Uruguay. Electronic address: mllofriualon@mail.usf.edu.
authors.forename: M
authors.initials: M
authors.lastname: Llofriu
authors.affiliation: Universidad de la Republica, Uruguay.
authors.forename: G
authors.initials: G
authors.lastname: Tejera
authors.affiliation: University of Arizona, United States.
authors.forename: M
authors.initials: M
authors.lastname: Contreras
authors.affiliation: University of Arizona, United States.
authors.forename: T
authors.initials: T
authors.lastname: Pelc
authors.affiliation: University of Arizona, United States.
authors.forename: J M
authors.initials: JM
authors.lastname: Fellous
authors.affiliation: University of South Florida, United States.
authors.forename: A
authors.initials: A
authors.lastname: Weitzenfeld
mesh_terms: D003071:Cognition; D006040:Goals; D006624:Hippocampus / Q000166:cytology / Q000502:physiology*; D006801:Humans; D007858:Learning; D008959:Models, Neurological; D012054:Reinforcement, Psychology; D012371:Robotics; D065854:Spatial Navigation / Q000502:physiology*
keywords: Hippocampus; Multiscale spatial representation; Place cells; Reinforcement learning; Spatial cognition model