Representing and Solving Decision Problems with Limited Information

Authors:
Steffen L. Lauritzen;Dennis Nilsson
Affiliations:
-;-
Venue:
Management Science
Year:
2001

Citing 0
Cited 25

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Efficiency of influence diagram models with continuous decision variables

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Modeling challenges with influence diagrams: Constructing probability and utility models

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Sequential decision making with partially ordered preferences

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Influence diagrams with memory states: representation and algorithms

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Unconstrained influence diagrams

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A Framework for Solving Hybrid Influence Diagrams Containing Deterministic Conditional Distributions

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Solving limited memory influence diagrams

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On the complexity of solving polytree-shaped limited memory influence diagrams with binary variables

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Abstract

We introduce the notion ofLImitedMemoryInfluenceDiagram (LIMID) to describe multistage decision problems in which the traditional assumption of no forgetting is relaxed. This can be relevant in situations with multiple decision makers or when decisions must be prescribed under memory constraints, such as in partially observed Markov decision processes (POMDPs). We give an algorithm for improving any given strategy by local computation of single policy updates and investigate conditions for the resulting strategy to be optimal.