A probabilistic model for interactive decision-making

作者:

摘要

A probabilistic reasoning model is defined where the decision maker (d.m.) is engaged in a sequential information-gathering process facing the trade-off between the reliability of the achieved solution and the associated observation cost. The d.m. is directly involved in the proposed flexible control strategy, which is based on information-theoretic principles. The devised strategy works on a Bayesian belief network that allows the efficient representation and manipulation of the knowledge base relevant to the problem domain. It is shown that this strategy guarantees a constant factor approximate solution with respect to the optimum of the decision problem. Some application examples are also discussed.

论文关键词:Decision-making under uncertainty,Information-gathering strategy,Myopic policy,Interactive solution procedure,Bayesian belief networks

论文评审过程:Accepted 20 January 1999, Available online 13 May 1999.

论文官网地址:https://doi.org/10.1016/S0167-9236(99)00013-5