Universal computation and physical dynamics
Proceedings of the conference on Chaos, order and patterns : aspects of nonlinearity---the "Gran Finale": aspects of nonlinearity---the "Gran Finale"
Introduction to artificial life
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A Mathematical Theory of Communication
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Models, simulations, instantiations, and evidence: the case of digital evolution
Journal of Experimental & Theoretical Artificial Intelligence - Selected Papers from the 2006 North American Computers and Philosophy Conference, Guest Editor: Patrick Grim
Evolutional Aspects of the Construction of Adaptive Knowledge Base
ISNN '09 Proceedings of the 6th International Symposium on Neural Networks on Advances in Neural Networks
Digital ecosystems: self-organisation of evolving agent populations
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ICSI'10 Proceedings of the First international conference on Advances in Swarm Intelligence - Volume Part I
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ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part V
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Whether or not Darwinian evolution leads to an increase in complexity depends crucially on what we mean by the term. Physical complexity is a measure based on automata theory and information theory that turns out to be a simple and intuitive measure of the amount of information that an organism stores, in its genome, about the environment in which it evolves. It can be shown that the physical complexity of the genomes of clonal organisms must increase in evolution, if they occupy a single niche and if the environment does not change. This law of increasing complexity is a consequence of natural selection only and can be violated in co-evolving systems as well as at high mutation rates, in sexual populations, and in time-dependent landscapes. Yet, co-evolution, because it can be viewed as creating an increase in physical complexity across niches, is likely the agent of a global increase in complexity.