Modeling Complex Processes Through Nature-Analogous Methods Artificial Intelligence and Artificial Life

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.

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.

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.