Introduction to Artificial Life

By C. Endres. Künstliche Intell., 2000

329 citations recorded by the source corpus.

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Dynamic multiobjective optimization problems: test cases, approximations, and applications (2004, methodology): “A promising method for dynamic optimization algorithm development seems to be the exploitation of an artificial life (A-life) paradigm (see [18] and [19] for a detailed overview) and the hybridization of it with evolutionary computation [20], [21].”
An information-theoretic primer on complexity, self-organization, and emergence (2009, background): “We are proposing here to clarify the applicability and exemplify how diﬀerent information channels can be identiﬁed and used.”
Supply-chain networks: a complex adaptive systems perspective (2005, background): “Such systems have been commonly referred to as Complex Systems (Baranger 2005, Bar-Yam 1997, Adami 1998, Flake 1998).”
How to Solve It: Modern Heuristics (2000, methodology): “The coevolutionary system started with a population of 15 neural networks, each one having its weighted connections and K value set at random in the range [1, 3].”
Information Theory of Complex Networks: On Evolution and Architectural Constraints (2004, background): “A closely related, and more general approach involves the use of information-based measures [19-21].”