TY - JOUR
T1 - Sequential decision making with partially ordered preferences
AU - Kikuti, Daniel
AU - Cozman, Fabio Gagliardi
AU - Filho, Ricardo Shirota
PY - 2011/5/1
Y1 - 2011/5/1
N2 - This paper presents new insights and novel algorithms for strategy selection in sequential decision making with partially ordered preferences; that is, where some strategies may be incomparable with respect to expected utility. We assume that incomparability amongst strategies is caused by indeterminacy/imprecision in probability values. We investigate six criteria for consequentialist strategy selection: Γ-Maximin, Γ-Maximax, Γ-Maximix, Interval Dominance, Maximality and E-admissibility. We focus on the popular decision tree and influence diagram representations. Algorithms resort to linear/multilinear programming; we describe implementation and experiments. © 2010 Elsevier B.V. All rights reserved.
AB - This paper presents new insights and novel algorithms for strategy selection in sequential decision making with partially ordered preferences; that is, where some strategies may be incomparable with respect to expected utility. We assume that incomparability amongst strategies is caused by indeterminacy/imprecision in probability values. We investigate six criteria for consequentialist strategy selection: Γ-Maximin, Γ-Maximax, Γ-Maximix, Interval Dominance, Maximality and E-admissibility. We focus on the popular decision tree and influence diagram representations. Algorithms resort to linear/multilinear programming; we describe implementation and experiments. © 2010 Elsevier B.V. All rights reserved.
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U2 - 10.1016/j.artint.2010.11.017
DO - 10.1016/j.artint.2010.11.017
M3 - Article
SN - 0004-3702
SP - 1346
EP - 1365
JO - Artificial Intelligence
JF - Artificial Intelligence
ER -