One of the important research challenges today is to develop new theoretical methods, algorithms, and implementations of systems with a higher level of flexibility and autonomy, we can say with higher level of intelligence. Intelligent systems should be dynamically evolving and be able to adapt and learn. That is, the system must be able to evolve, to self-develop, to self-organize, to self-evaluate and to self-improve. The emerging area of Evolving Intelligent Systems targets non-stationary processes by developing novel on-line learning methods and computationally efficient algorithms for real-time applications. Some of the natural implementation areas of Evolving and Adaptive Intelligent systems are: wireless sensor networks, assisted ambient intelligence, embedded soft computing diagnostics and prognostics algorithms, intelligent agents, smart evolving sensors, autonomous robotic systems etc.