This volume describes our intellectual path from the physics of complex
sys- tems to the science of artificial cognitive systems. It was
exciting to discover that many of the concepts and methods which succeed
in describing the self- organizing phenomena of the physical world are
relevant also for understand- ing cognitive processes. Several nonlinear
physicists have felt the fascination of such discovery in recent years.
In this volume, we will limit our discussion to artificial cognitive
systems, without attempting to model either the cognitive behaviour or
the nervous structure of humans or animals. On the one hand, such
artificial systems are important per se; on the other hand, it can be
expected that their study will shed light on some general principles
which are relevant also to biological cognitive systems. The main
purpose of this volume is to show that nonlinear dynamical systems have
several properties which make them particularly attractive for reaching
some of the goals of artificial intelligence. The enthusiasm which was
mentioned above must however be qualified by a critical consideration of
the limitations of the dynamical systems approach. Understanding
cognitive processes is a tremendous scientific challenge, and the
achievements reached so far allow no single method to claim that it is
the only valid one. In particular, the approach based upon nonlinear
dynamical systems, which is our main topic, is still in an early stage
of development.