Theory and Applications of Bioinspired Neural Intelligence for Robotics and Control

Abstract

Computational intelligence approaches are nature-inspired methods, which offer a wealth of ideas for solutions to complex problems. In comparison to the traditional approaches, the computational intelligence approaches are more powerful so that they do not need the reformulation of the problem to search a nonlinear and a nondifferentiable space with real world conditions with the massive parallelism. Another advantage of the computational intelligence approaches is the flexibility of the fitness function formulation, which can be expressed as a proper function of the system outputs and are suitable for multiobjective problems.