Complex Systems and the Evolution of Artificial Intelligence

Abstract

All kinds of complex dynamical systems can be modeled by computational systems (Sect. 6.1). Their concepts are inspired by the successful technical applications of nonlinear dynamics to solid-state physics, spin-glass physics, chemical parallel computers, optical parallel computers, laser systems, and the human brain (Sect. 6.2). The cellular neural network (CNN) model has recently become an influential paradigm in complexity research (Sect. 6.3). Like the universal Turing machine model for digital computers, there is a universal CNN machine for modeling analog neural computers. CNNs are used not only for pattern recognition, but to simulate various types of pattern formation (Sect. 6.4). Exciting applications of artificial neural networks already exist in the fields of organic computing, neurobionics, medicine, and robotics (Sect. 6.5). Natural life and intelligence depends decisively on the evolution of organisms and brains. Therefore, embodied life and mind lead to embodied artificial intelligence and embodied artificial life of embodied robotics (Sect. 6.6).