Computing Anticipatory Systems

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Computing Anticipatory Systems is written by D. Dubois and published by American Institute of Physics. It's available with International Standard Book Number or ISBN identification 0735405794 (ISBN 10) and 9780735405790 (ISBN 13).

These proceedings deal with a selection of papers presented at the 8th International Conference CASYS’07, on COMPUTING ANTICIPATORY SYSTEMS, 6-11 August 2007, held at HEC Management School - University of Liege, Liège, Belgium. The content of these proceedings deals with the most recent Research & Development in the area of theoretical developments and applications in the modelling and computing of anticipation in any fields of natural and artificial systems. A computing anticipatory system is a system that computes its current states in taking into account its past and present states but also its potential future states. Strong anticipation refers to an anticipation of events built by or embedded in a system. Weak anticipation refers to an anticipation of events predicted or forecasted from a model of a system. This volume contains the first invited lecture “Neural Approach to Machine Consciousness”, by Prof. Dr Igor Aleksander, FREng (UK) who received the CHAOS AWARD, and the second invited lecture “Quantum Mechanics, Pattern Recognition, and the Mammalian Brain”, by Dr George Chapline (USA) who received the CASYS AWARD. The peer reviewed papers that received a BEST PAPER AWARD at CASYS’07, and some invited papers are included in these proceedings. Adel F. Antippa (Canada) and Daniel M. Dubois (Belgium) presented the continuation of their original research project on discrete physics with their third fundamental paper “Synchronous Discrete Harmonic Oscillator” that also appears in these proceedings. The interdisciplinary outstanding topics of these proceedings are readable by researchers and scientists with a university background.