We study an economic decision problem where the actors are two firms and the Antitrust Authority whose main task is to monitor and prevent firms’ potential anti-competitive behaviour and its effect on the market. The Antitrust Authority’s decision process is modelled using a Bayesian network where both the relational structure and the parameters of the model are estimated from a data set provid...

detection of oil-water contacts (owcs) is one of the primary tasks before evaluation of reservoir’s hydrocarbon in place, determining net pay zones and suitable depths for perforation operation. this paper introduces bayesian decision making tool as an effective technique in owc detecting using wire line logs. to compare strengths of the suggested method in detecting owc with conventional one, ...

A decision model, stemmed from Bayesian thinking, is proposed to predict the operator’s behavior in manufacturing system. The decision model is addressed using non-parametric distribution where a binary division method is proposed to reduce the complexity of the model, eliminating irrelevant features.

The development of new and improved Information Technology (IT) methods for Supply Chain Management is important. Existing methods suffer from several shortcomings, especially the ability to deal with a mixture of quantitative and qualitative data. This study aims to apply decision support techniques to the area of Supply Chain Management in order to address some of the shortcomings. The method...

Many important real-world decision-making problems involve group interactions among individuals with purely informational externalities. Such situations arise for example in jury deliberations, expert commiŠees, medical diagnoses, etc. We model the purely informational interactions of rational agents in a group, where they receive private information and act based on that information while also...

For any tourism organisation or company, it is a necessity to know about the factors that are influencing tourists’ travel decisions. The question, however, is how to model and represent heterogeneous influence factors in a way that a) human decision makers can easily understand, and b) allows for computer-based simulation and diagnoses to aid decision making. Currently, tourism suffers from me...

Two approaches for bidding in games are presented: knowledge-based approach and simulation-based approach. A general knowledge-based decision model for bidding in games with its strategy encoded in a Bayesian network was designed. A program for playing four-player tarok was implemented incorporating a specialised instance of the decision model and a simulation module for bidding. Both approache...

Abstract: The paper concerns a cooperation problem in multiple participant decision making (DM). A fully scalable cooperation model with individual participants being Bayesian decision makers who use fully probabilistic design of the optimal decision strategy is presented. The solution suggests a flat structure of cooperation, where each participant interacts with several ‘neighbours’. The coop...

This paper deals with the utilizing of Binary Decision Diagrams built on the Bayes-Dirichlet metric for representation of logic functions. In the first phase the Binary Decision Tree is built followed by a reduction process resulted in binary decision diagram (BDD). The BDDs are also used as a probabilistic model for advanced Bayesian decomposer for digital circuit partitioning. It is shown tha...