Knowledge incorporation in evolutionary computation This carefully edited book puts together the state of the art and recent advances in knowledge incorporation in evolutionary computation within a unified framework. The book provides a comprehensive self contained view of knowledge incorporation in evolutionary computation including a concise introduction to evolutionary algorithms as well as knowledge representation methods.&nbsp; Knowledge Incorporation in Evolutionary&nbsp;Computation is a valuable reference for researchers students and professionals from engineering and computer science in particular in the areas of artificial intelligence soft computing natural computing and evolutionary computation. TOC:From the Contents: Part I Introduction. A Selected Introduction to Evolutionary Computation. Part II Knowledge Incorporation in Initialization Recombination and Mutation. The Use of Collective Memory in Genetic Programming. A Cultural Algorithm for Solving the Job Shop Scheduling Problem. Part III Knowledge Incorporation in Selection and Reproduction. Learning Probabilistic Models for Enhanced Evolutionary Computation. Probabilistic Models for Linkage Learning in Forest Management. Part IV Knowledge Incorporation in Fitness Evaluations. Neural Networks for Fitness Approximation in Evolutionary Optimization. Part V Knowledge Incorporation through Life time Learning and Human Computer Interactions. Knowledge Incorporation Through Lifetime Learning. Part VI Preference Incorporation in Multi objective Evolutionary Computation. Integrating User Preferences into Evolutionary Multi Objective Optimization