"Theory and New Applications of Swarm Intelligence" ed. by Rafael Parpinelli and Heitor S. Lopes (Repost)

This book presents some recent advances on Swarm Intelligence, specially on new swarm-based optimization methods and hybrid algorithms for several applications.

The field of research that studies the emergent collective intelligence of self-organized and decentralized simple agents is referred to as Swarm Intelligence. It is based on social behavior that can be observed in nature, such as flocks of birds, fish schools and bee hives, where a number of individuals with limited capabilities are able to come to intelligent solutions for complex problems.
The computer science community have already learned about the importance of emergent behaviors for complex problem solving.

The content of this book allows the reader to know more both theoretical and technical aspects and applications of Swarm Intelligence.

Contents
1 Swarm-Based Metaheuristic Algorithms and No-Free-Lunch Theorems
2 Analysis of the Performance of the Fish School Search Algorithm Running in Graphic Processing Units
3 Social Emotional Optimization Algorithm with Random Emotional Selection Strategy
4 The Pursuit of Evolutionary Particle Swarm Optimization
5 Volitive Clan PSO - An Approach for Dynamic Optimization Combining Particle Swarm Optimization and Fish School Search
6 Inverse Analysis in Civil Engineering: Applications to Identification of Parameters and Design of Structural Material Using Mono or Multi-Objective Particle Swarm Optimization
7 Firefly Meta-Heuristic Algorithm for Training the Radial Basis Function Network for Data Classification and Disease Diagnosis
8 Under-Updated Particle Swarm Optimization for Small Feature Selection Subsets from Large-Scale Datasets
9 Predicting Corporate Forward 2 Month Earnings