Information Processing with Evolutionary Algorithms : From Industrial Applications to Academic Speculations / edited by Xindong Wu, Lakhmi Jain, Manuel Graña, Richard J. Duro, Alicia d’Anjou, Paul P. Wang.

Springer eBooks

Adaptive Business Intelligence Based on Evolution Strategies: Some Application Examples of Self-Adaptive Software -- Extending the Boundaries of Design Optimization by Integrating Fast Optimization Techniques with Machine Code Based, Linear Genetic Programming -- Evolutionary Optimization of Approximating Triangulations for Surface Reconstruction from Unstructured 3D Data -- An Evolutionary Algorithm Based on Morphological Associative Memories for Endmember Selection in Hyperspectral Images -- On a Gradient-based Evolution Strategy for Parametric Illumination Correction -- A New Chromosome Codification for Scheduling Problems -- Evolution-based Learning of Ontological Knowledge for a Large-scale Multi-agent Simulation -- An Evolutionary Algorithms Approach to Phylogenetic Tree Construction -- Robot Controller Evolution with Macroevolutionary Algorithms -- Evolving Natural Language Grammars -- Evaluating Protein Structure Prediction Models with Evolutionary Algorithms -- Learning Decision Rules by Means of Hybrid-Encoded Evolutionary Algorithms -- Evolvable Hardware Techniques for Gate-Level Synthesis of Combinational Circuits -- The Evolutionary Learning Rule in System Identification -- Current and Future Research Trends in Evolutionary Multiobjective Optimization -- Genetic Algorithms with Limited Convergence -- Evolution with Sampled Fitness Functions -- Molecular Computing by Signaling Pathways -- Strategy-Oriented Evolutionary Games: Toward a Grammatical Model of Games -- Discrete Multi-Phase Particle Swarm Optimization.

The last decade of the twentieth century has witnessed a surge of interest in numerical, computational intensive approaches to information processing. The lines that draw the boundaries between statistics, optimization, artificial intelligence and information processing are disappearing and it is not uncommon to find well founded and sophisticated mathematical approaches in applications traditionally associated with ad-hoc programming. Evolutionary Algorithms are increasingly being applied to information processing applications that require any kind of optimization and they have reached the status of problem-solving tools in the backpack of the engineer. However, there are still exciting new developments taking place in the academic community. The driving idea in the organization of this edited volume is the emphasis in the contrast between already accepted engineering practice and on-going explorations in the academic community. As From industrial applications to academic speculations suggests, the organization of Information Processing with Evolutionary Algorithms follows an axis of nearness to practical applications, travelling from industrial day-to-day problems and practice to the more speculative works.

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