Event Date/Time: Sep 25, 2007 End Date/Time: Sep 30, 2007
Registration Date: Jul 25, 2007
Early Registration Date: Jun 15, 2007
Abstract Submission Date: Jul 15, 2007
Paper Submission Date: Jul 15, 2007
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The natural world ruled by the laws of physics and the knowledge world ruled by the laws of information theory share very deep similarities and analogies arising from the equivalence and convergence between the elemen-tary units of their worlds and statistical mechanisms of their interaction at different levels of course graining.
Already in the quantum world where quants and bits be-come the same entities a new discipline of quantum computing emerges trying to exploit the natural parallel-ism to ultra fast search algorithms and simulations of quantum processes. At the micro scale particles and data share similar statistical properties of entropy and uncertainty and physical processes at this level guide variety of optimisation techniques like particle filters, simulated annealing, stochastic diffusion search, and learning methods like mutual information maximisation, stochastic Boltzman learning or particle dynamics-based learning. Finally in the natural macro world, interacting living organisms with their brains, complex multimodal sensing mechanisms and social organisations continue to guide and inspire large scale simulatory optimisation techniques and are at the heart of genetic algorithms, evolutionary computation, particle swarm optimisation, ant colony optimizations and many other hybrid methods
The goal of NIML Special Session is to gather together all different interfaces between information theory and natural sciences: physics, biology, chemistry to properly identify, describe and propose new mechanisms of artifi-cial learning that would be directly guided by the natural physical or social processes/phenomena. The research scope covered by this session includes but is not limited to the following themes:
• Analogies between physical/natural sciences and information theory
• Physical limits of information acquisition, processing and transmitting
• Quantum information processing
• Simulated Annealing
• Stochastic Diffusion Search
• Stochastic Boltzman Learning
• Particle Swarm and Ant Colony Optimisation
• Genetic Algorithms & Evolutionary Computation
• Particle Filters
• Particle Dynamics-based Learning
• Information Theoretic Learning, Mutual Informa-tion Maximisation
• Algorithmic Kolmogorov Complexity
• Social Networks



Additional Information

Original contributions summarised in a form of short (3-4 A4 pages) papers covering or comprehending the above do-mains are welcome for submission to be presented at the ICCMSE’2007 conference and subsequently published in the famous AIP Conference Proceedings Series. Authors of the selected papers will be invited to submit an extended version to AIP and affiliated journals. Instructions for the format and paper preparations along with the template files can be found in: http://www.iccmse.org/proceeding.htm. Short papers should be submitted no later than July 15, 2007 to Dr Dymitr Ruta (dymitr.ruta@bt.com) For fees, accommodation and other information please refer to the conference website: http://www.iccmse.org