Logical methods in artificial intelligence applications

Bayesian Methods in Artificial Intelligence

In many problems in the area of artificial intelligence, it is necessary to deal with uncertainty. Using probabilistic models can also improve efficiency of standard AI-based techniques. Commonly used methods for dealing with uncertainty include Bayesian models, which can be used to describe and work with probabilistic systems effectively. This article reviews several models based on the Bayesi...

Mathematical methods in artificial intelligence

Advances in Artificial Intelligence Applications

We introduce a complex decision-making problem, the prioritizationof potential high-profit category segments to be sourced from low cost coun-tries, where several conflicting criteria must be taken into account simultane-ously to help focus the attention on developing low cost countries sourcingstrategies for candidate segments, where potential savings are higher and risk is...

Artificial Intelligence Methods and Techniques for Business and Engineering Applications

The problem for existence and determination of the set of positive asymptotically stable realizations of a proper transfer function of linear continuous-time systems is formulated and solved. Necessary and sufficient conditions for existence of the set of the realizations are established. Procedure for computation of the set of realizations are proposed and illustrated by numerical examples.

Artificial Intelligence Methods for Ambient Intelligence

Ambient Intelligence (ISTAG (2001) Scenarios for Ambient Intelligence in 2010) is a vision that enables intelligent environments with pervasive technology. In this vision human users are at the cent re, but machine and human are seen as equal, collaborating, to improve both human being and machine performance. Ambient Intelligence offers many benefits. For example, by inst rumenting public and ...