New Hybrid Intelligent Systems to Solve Linear and Quadratic Optimization Problems and Increase Guaranteed Optimal Convergence Speed of Recurrent ANN -- A Novel Optimization Algorithm Based on Reinforcement Learning -- The Use of Opposition for Decreasing Function Evaluations in Population-Based Search -- Search Procedure Exploiting Locally Regularized Objective Approximation. A Convergence Theorem for Direct Search Algorithms -- Optimization Problems with Cardinality Constraints -- Learning Global Optimization Through a Support Vector Machine Based Adaptive Multistart Strategy -- Multi-Objective Optimization Using Surrogates -- A Review of Agent-Based Co-Evolutionary Algorithms for Multi-Objective Optimization -- A Game Theory-Based Multi-Agent System for Expensive Optimisation Problems -- Optimization with Clifford Support Vector Machines and applications -- A Classification method based on principal component analysis and differential evolution algorithm applied for prediction diagnosis from clinical EMR heart data sets -- An Integrated Approach to Speed Up GA-SVM Feature Selection Model -- Computation in Complex Environments; -- Project Scheduling: Time-Cost Tradeoff Problems -- Systolic VLSI and FPGA Realization of Artificial Neural Networks -- Application of Coarse-Coding Techniques for Evolvable Multirobot Controllers.

This volume presents a collection of recent studies covering the spectrum of computational intelligence applications with emphasis on their application to challenging real-world problems. Topics covered include: Intelligent agent-based algorithms, Hybrid intelligent systems, Cognitive and evolutionary robotics, Knowledge-Based Engineering, fuzzy sets and systems, Bioinformatics and Bioengineering, Computational finance and Computational economics, Data mining, Machine learning, and Expert systems. "Computational Intelligence in Optimization" is a comprehensive reference for researchers, practitioners and advanced-level students interested in both the theory and practice of using computational intelligence in real-world applications.