A symbolic algebra for the computation of expected utilities in multiplicative influence diagrams

Leonelli, M., Riccomagno, E. and Smith, J. Q. (2017) A symbolic algebra for the computation of expected utilities in multiplicative influence diagrams. Annals of Mathematics and Artificial Intelligence, 81(3-4), pp. 273-313. (doi: 10.1007/s10472-017-9553-y)

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Influence diagrams provide a compact graphical representation of decision problems. Several algorithms for the quick computation of their associated expected utilities are available in the literature. However, often they rely on a full quantification of both probabilistic uncertainties and utility values. For problems where all random variables and decision spaces are finite and discrete, here we develop a symbolic way to calculate the expected utilities of influence diagrams that does not require a full numerical representation. Within this approach expected utilities correspond to families of polynomials. After characterizing their polynomial structure, we develop an efficient symbolic algorithm for the propagation of expected utilities through the diagram and provide an implementation of this algorithm using a computer algebra system. We then characterize many of the standard manipulations of influence diagrams as transformations of polynomials. We also generalize the decision analytic framework of these diagrams by defining asymmetries as operations over the expected utility polynomials.

Item Type:Articles
Additional Information:Manuele Leonelli was funded by Capes, whilst J.Q. Smith was partly supported by EPSRC grant EP/K039628/1 and The Alan Turing Institute under EPSRC grant EP/N510129/1.
Glasgow Author(s) Enlighten ID:Leonelli, Dr Manuele
Authors: Leonelli, M., Riccomagno, E., and Smith, J. Q.
College/School:College of Science and Engineering > School of Mathematics and Statistics > Statistics
Journal Name:Annals of Mathematics and Artificial Intelligence
ISSN (Online):1573-7470
Published Online:21 June 2017
Copyright Holders:Copyright © 2017 The Authors
First Published:First published in Annals of Mathematics and Artificial Intelligence 81(3-4): 273-313
Publisher Policy:Reproduced under a Creative Commons License

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