Publications (1)0 Total impact
ABSTRACT: This paper summarizes the research on population-based probabilistic search algorithms based on modeling promising solutions by estimating their probability distribution and using the constructed model to guide the further exploration of the search space. It settles the algorithms in the field of genetic and evolutionary computation where they have been originated. All methods are classified into a few classes according to the complexity of the class of models they use. Algorithms from each of these classes are briefly described and their strengths and weaknesses are discussed. 1 Introduction Recently, a number of evolutionary algorithms that guide the exploration of the search space by building probabilistic models of promising solutions found so far have been proposed. These algorithms have shown to perform very well on a wide variety of problems. However, in spite of a few attempts to do so, the field lacks a global overview of what has been done and where the research in th...