The duality of utility and information in optimally learning systems.

Belavkin, Roman V. ORCID logoORCID: https://orcid.org/0000-0002-2356-1447 (2008) The duality of utility and information in optimally learning systems. In: IEEE Systems, Man and Cibernetics Society, UK and Republic of Ireland: 7th conference on cybernetics intelligent systems, 2008., 8th-9th September 2008, Middlesex University, London. . [Conference or Workshop Item]

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Abstract

The paper considers learning systems as optimisation
systems with dynamical information constraints, and general
optimality conditions are derived using the duality between
the space of utility functions and probability measures. The increasing dynamics of the constraints is used to parametrise the optimal solutions which form a trajectory in the space of probability measures. Stochastic processes following such trajectories describe systems achieving the maximum possible utility gain with respect to a given information. The theory is discussed on examples for finite and uncountable sets and in relation to existing applications and cognitive models of learning.

Item Type: Conference or Workshop Item (Paper)
Research Areas: A. > School of Science and Technology > Computer Science
A. > School of Science and Technology > Computer Science > Artificial Intelligence group
Item ID: 3491
Useful Links:
Depositing User: Dr Roman Belavkin
Date Deposited: 24 Mar 2010 10:31
Last Modified: 16 Jun 2022 01:35
URI: https://eprints.mdx.ac.uk/id/eprint/3491

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