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Action Discovery and Intrinsic Motivation: A Biologically Constrained Formalisation

Authors :
Ashvin Shah
Kevin Gurney
Nathan F. Lepora
Ansgar Koene
Peter Redgrave
Source :
Intrinsically Motivated Learning in Natural and Artificial Systems ISBN: 9783642323744, Intrinsically Motivated Learning in Natural and Artificial Systems
Publication Year :
2012
Publisher :
Springer Berlin Heidelberg, 2012.

Abstract

We introduce a biologically motivated, formal framework or “ontology” for dealing with many aspects of action discovery which we argue is an example of intrinsically motivated behaviour (as such, this chapter is a companion to that by Redgrave et al. in this volume). We argue that action discovery requires an interplay between separate internal forward models of prediction and inverse models mapping outcomes to actions. The process of learning actions is driven by transient changes in the animal’s policy (repetition bias) which is, in turn, a result of unpredicted, phasic sensory information (“surprise”). The notion of salience as value is introduced and broken down into contributions from novelty (or surprise), immediate reward acquisition, or general task/goal attainment. Many other aspects of biological action discovery emerge naturally in our framework which aims to guide future modelling efforts in this domain.

Details

ISBN :
978-3-642-32374-4
ISBNs :
9783642323744
Database :
OpenAIRE
Journal :
Intrinsically Motivated Learning in Natural and Artificial Systems ISBN: 9783642323744, Intrinsically Motivated Learning in Natural and Artificial Systems
Accession number :
edsair.doi...........ed8ec92f0d098dadff351dc74d38edb6
Full Text :
https://doi.org/10.1007/978-3-642-32375-1_7