Abstract
A computational model of the Basal Ganglia and the Hippocampus as key players in solving a navigation task is presented. The roles played by the above-mentioned neural substrates in navigation are demonstrated by an exploration task performed by a model rat in a simulated Morris Water Maze. To highlight the role of hippocampus in navigation, the agent is made to adopt a context-based navigation strategy. To demonstrate the role of BG in navigation, the agent is made to adopt a visual cue-based navigation strategy. The models are developed based on actor-critic architecture and trained using reinforcement learning. The above two models are integrated into a complete model which incorporates the above two forms of navigation.
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