Decision circuits perform efficient evaluation of influence diagrams, building on the advances in arithmetic circuits for belief network inference [Darwiche, 2003; Bhattacharjya and Shachter, 2007]. We show how even more compact decision circuits can be constructed for dynamic programming in influence diagrams with separable value functions and conditionally independent subproblems. Once a deci...

the concept of decision making, factors influencing it and the related outcomes have always attracted researchers. the purpose of this study is to investigate the effect of sacred values on decision making, decision difficulty and the resulting negative emotions. thus, a sample of 288 students from the university of guilan were chosen as subjects and were required to complete a standard questio...

Most areas of engineering, science, and management use important tools based on probabilistic methods. The common thread of the entire spectrum of these tools is aiding in decision making under uncertainty: the choice of an interpretation of reality or the choice of a course of action. Although the importance of dealing with uncertainty in decision making is widely acknowledged, dissemination o...

In this paper, we introduce an approach called RTBSS (RealTime Belief Space Search) for real-time decision making in large POMDPs. The approach is based on a look-ahead search that is applied online each time the agent has to make a decision. RTBSS is particularly interesting for large real-time environments where offline solutions are not applicable because of their complexity.

Cristiano Castelfranchi and Rino Falcone introduced an influential cognitive theory of social trust that is based on the concepts of belief, goal, ability, willingness and opportunity. In this paper we propose a simple logic of belief and action that allows to express these concepts. While our logic of belief is standard, our logic of action has a very simple kind actions: actions setting the t...

In this paper, an extension of the belief Analytic Hierarchy Process (AHP) method is proposed, based on the belief function framework. It takes into account the fact that the pair-wise comparison between criteria and alternatives may be uncertain and imprecise. Therefore, it introduces a new way to cope with expert judgments. Thus to express his preferences, the decision maker is allowed to use...

This paper shows that a unique and additive subjective belief can be derived from choice behavior that reveals Ellsberg-type ambiguity aversion. This belief is obtained as a component of a utility representation where subjective probabilities are contaminated by an exogenous information set. This representation delivers a parameter that is interpretable as a degree of the decision maker’s confi...

We propose a measure of the degree of ambiguity associated with a belief function and a nonparametric method to estimate it. The degree of ambiguity associated with a belief function is measured by the Kullback-Leibler diameter of the set of probability measures compatible with it. It is shown that an estimator based on the empirical version of the unambiguous measure generating the belief func...

Belief Networks in the Bayesian approach provide a wellestablished methodology to fuse prior knowledge and statistical observations for an enriched decision support. In this paper we investigate one of the advantages of the Bayesian approach the provided additional uncertainty information for predictions in a medical classification problem. We perform a Bayesian analysis using Belief Network mo...