
Type of publication:  Inproceedings 
Entered by:  JOSM 
Title  An Introduction to stochastic control theory, path integrals and reinforcement learning 
Bibtex cite ID  
Booktitle  Proceedings 9th Granada Seminar on Computational Physics: Computational and Mathematical Modeling of Cooperative Behavior in Neural Systems 
Year published  2006 
Month  September 
Location  1115 September 2006, Granada, Spain 
Keywords  stochastic control theory,path integrals,reinforcement learning 
Abstract  Control theory is a mathematical description of how to act optimally to gain future rewards. In this paper I give an introduction to deterministic and stochastic control theory and I give an overview of the possible application of control theory to the modeling of animal behavior and learning. I discuss a class of nonlinear stochastic control problems that can be efficiently solved using a path integral or by MC sampling. In this control formalism the central concept of costtogo becomes a free energy and methods and concepts from statistical physics can be readily applied. 
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