May 14, 2014

Collecting reward to defend homeostasis: A homeostatic reinforcement learning theory

BioRxiv : the Preprint Server for Biology
Mehdi Keramati, Boris Gutkin

Abstract

Efficient regulation of internal homeostasis and defending it against perturbations requires complex behavioral strategies. However, the computational principles mediating brain’s homeostatic regulation of reward and associative learning remain undefined. Here we use a definition of primary rewards, as outcomes fulfilling physiological needs, to build a normative theory showing how learning motivated behavior is modulated by the internal state of the animal. The theory proves that seeking rewards is equivalent to the fundamental objective of physiological stability, defining the notion of physiological rationality of behavior. We further give a formal basis for temporal discounting of reward. It also explains how animals learn to act predictively to preclude prospective homeostatic challenges, and attributes a normative computational role to the modulation of midbrain dopaminergic activity by hypothalamic signals.

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Mentioned in this Paper

Regulation of Biological Process
Definition
Brain
Learning Theory
Entire Midbrain
Challenge
Regulation of Homeostatic Process
Learning
Reinforcement Surgical Repair
Midbrain Structure

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