An introduction to stochastic control theory, path integrals and reinforcement learning
In: AIP, 11-15 September 2006, Spain.
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 non-linear stochastic control problems that can be efciently solved
using a path integral or by MC sampling. In this control formalism the central concept of cost-to-go
becomes a free energy and methods and concepts from statistical physics can be readily applied.
Keywords: Stochastic optimal control, path integral control, reinforcement learning
PACS: 05.45.-a 02.50.-r 45.80.+r