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The Role of the Basal Ganglia in Exploratory Behavior in a Model Based on Reinforcement Learning

  • Sridharan Devarajan
  • P. S. Prashanth
  • V. S. Chakravarthy
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3316)

Abstract

We present a model of basal ganglia as a key player in exploratory behavior. The model describes exploration of a virtual rat in a simulated “water pool” experiment. The virtual rat is trained using a reward-based or reinforcement learning paradigm which requires units with stochastic behavior for exploration of the system’s state space. We model the STN-GPe system as a pair of neuronal layers with oscillatory dynamics, exhibiting a variety of dynamic regimes like chaos, traveling waves and clustering. Invoking the property of chaotic systems to explore a state space, we suggest that the complex “exploratory” dynamics of STN-GPe system in conjunction with dopamine-based reward signaling present the two key ingredients of a reinforcement learning system.

Keywords

Basal Ganglion Output Layer Exploratory Behavior Effective Dimension Water Pool 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Sridharan Devarajan
    • 1
  • P. S. Prashanth
    • 1
  • V. S. Chakravarthy
    • 1
  1. 1.Department of Aerospace Engineering and Department of Electrical EngineeringIndian Institute of TechnologyMadrasIndia

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