The paper presents a method for generating solutions of a constraint satisfaction problem (CSP) uniformly at random. The main idea is to express the CSP as a factored probability d...
Until now, AI argumentation-based systems have been mainly developed for handling inconsistency. In that explanation-oriented perspective, only one type of argument has been consi...
Abstract. This paper evaluates the power of a new scheme that generates search heuristics mechanically. This approach was presented and evaluated rst in the context of optimization...
Belief Propagation (BP) can be very useful and efficient for performing approximate inference on graphs. But when the graph is very highly connected with strong conflicting intera...
Many problems require repeated inference on probabilistic graphical models, with different values for evidence variables or other changes. Examples of such problems include utilit...