Here is a comprehensive presentation of methodology for the design and
synthesis of an intelligent complex robotic system, connecting formal
tools from discrete system theory, artificial intelligence, neural
network, and fuzzy logic. The necessary methods for solving real time
action planning, coordination and control problems are described. A
notable chapter presents a new approach to intelligent robotic agent
control acting in a realworld environment based on a lifelong learning
approach combining cognitive and reactive capabilities. Another key
feature is the homogeneous description of all solutions and methods
based on system theory formalism.