Modeling Complex Processes Through Nature-Analogous Methods

This book is an introduction to nature-analogous techniques and related formal methods. For each technique, application examples are provided. It covers cellular automata and Boolean networks, evolutionary algorithms, as well as simulated annealing, fuzzy methods, neural networks, and finally hybrid systems, i.e., combinations of various techniques. Based on the theory of complex dynamic systems, theoretical foundations are also presented, and the similarities of these seemingly very heterogeneous techniques are pointed out. The edition has been revised and expanded with current trends such as ChatGPT.

Content

Bottom-up models, complex systems, and nature-analogous methods of AI and AL
Self-organizing systems: cellular automata, Boolean networks, and neighborhood generating algorithms
The modeling of adaptive processes through evolutionary algorithms
Modeling learning systems through neural networks
Modeling the imprecise: fuzzy set theory and fuzzy logic
Hybridizations of the basic models
Summary and perspectives



Target Audience

Students, educators, and practitioners interested in new modeling with methods of Artificial Intelligence and Artificial Life for their professional activities.

Authors

PD Dr. Christina Klüver, Prof. Dr. Jürgen Klüver, and Dr. Jörn Schmidt form the research group COBASC (Computer Based Analysis of Social Complexity). They developed numerous computer programs for the simulation and analysis of complex processes.

The translation was done with the help of artificial intelligence. A subsequent human revision was done primarily in terms of content.

This book is a translation of an original German edition. The translation was done with the help of artificial intelligence (machine translation by the service DeepL.com). A subsequent human revision was done primarily in terms of content, so that the book will read stylistically differently from a conventional translation.