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GECCO
2006
Springer
195views Optimization» more  GECCO 2006»
13 years 11 months ago
Studying XCS/BOA learning in Boolean functions: structure encoding and random Boolean functions
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...
Martin V. Butz, Martin Pelikan
AIIA
2003
Springer
14 years 19 days ago
Improving the SLA Algorithm Using Association Rules
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,...
IJAR
2006
89views more  IJAR 2006»
13 years 7 months ago
Learning probabilistic decision graphs
Probabilistic decision graphs (PDGs) are a representation language for probability distributions based on binary decision diagrams. PDGs can encode (context-specific) independence...
Manfred Jaeger, Jens D. Nielsen, Tomi Silander
ECAI
2008
Springer
13 years 9 months ago
Structure Learning of Markov Logic Networks through Iterated Local Search
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...
Marenglen Biba, Stefano Ferilli, Floriana Esposito
CSCLP
2006
Springer
13 years 11 months ago
Efficient Recognition of Acyclic Clustered Constraint Satisfaction Problems
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...
Igor Razgon, Barry O'Sullivan