Recently, studies with the XCS classifier system on Boolean functions have shown that in certain types of functions simple crossover operators can lead to disruption and, conseque...
A bayesian network is an appropriate tool for working with uncertainty and probability, that are typical of real-life applications. In literature we find different approaches for b...
Evelina Lamma, Fabrizio Riguzzi, Andrea Stambazzi,...
Probabilistic decision graphs (PDGs) are a representation language for probability distributions based on binary decision diagrams. PDGs can encode (context-specific) independence...
Many real-world applications of AI require both probability and first-order logic to deal with uncertainty and structural complexity. Logical AI has focused mainly on handling com...
Abstract. In this paper we present a novel approach to solving Constraint Satisfaction Problems whose constraint graphs are highly clustered and the graph of clusters is close to b...