Revisão Bibliográfica: Autômatos Celulares
Download 445.54 Kb.
|
- Navigate this page:
- Internet
- Fonte: http://www.santafe.edu/projects/evca/
- Title: The Evolution of Emergent Computation
- Title: Embedded-Particle Computation in Evolved Cellular Automata
- Title: Mechanisms of Emergent Computation in Cellular Automata
- 2.2) Softwares
Referências em Papel:
Internet:
Fonte: http://www.santafe.edu/projects/evca/Title: Dynamics, Emergent Computation, and Evolution in Cellular AutomataAuthor: Wim Hordijk Reference: Ph. D. Thesis, University of New Mexico, Albuquerque, NM, December 1999. SFI working paper: LANL archive: Abstract: A new class of models is developed which provides a tool for analyzing emergent computation in cellular automata (CAs). In particular, CAs that were evolved with a genetic algorithm to perform computational tasks requiring global information processing are analyzed. The models are used to make quantitative predictions of the computational performance, on a given task, of these evolved CAs. The models, and the resulting performance predictions, are based on the (emergent) dynamics of the evolved CAs and thus relate the dynamics of these CAs directly to their emergent computational abilities. Furthermore, the class of models is used to determine quantitatively how and to what extent changes in the emergent dynamics of a CA give rise to changes in its performance. In particular, the differences between the dynamics of CAs that are related to each other in an evolutionary sense are analyzed this way. This, in turn, contributes to a better understanding of the evolution of emergent computation in CAs. Finally, the class of models itself is investigated more thoroughly. For example, a correctness proof of the models is presented and an expression for scaling the models to larger system sizes is derived. The development, application, and investigation of this class of models thus forms a study of, and provides a better understanding of, the relation among dynamics, emergent computation, and evolution in cellular automata.
Reference: Proceedings of the National Academy of Sciences, USA 92, 23:10742-10746, 1995. SFI working paper: 94-03-012 LANL archive: Abstract: A simple evolutionary process can discover sophisticated methods for emergent information processing in decentralized spatially-extended systems. The mechanisms underlying the resulting emergent computation are explicated by a novel technique for analyzing particle-based logic embedded in pattern-forming systems. Understanding how globally-coordinated computation can emerge in evolution is relevant both for the scientific understanding of natural information processing and for engineering new forms of parallel computing systems. Title: Embedded-Particle Computation in Evolved Cellular AutomataAuthors: Wim Hordijk, James P. Crutchfield, and Melanie Mitchell Reference: In T. Toffoli, M Biafore, and J. Leão (eds.), Physics and Computation '96 (Pre-proceedings), New England Complex Systems Institute, 153-158, 1996. SFI working paper: 96-09-073 LANL archive: Abstract:In previous work, we analyzed the process by which a genetic algorithm designed CAs to perform particular tasks. In this paper we focus on how these Cas implement the emergent computational strategies for performing a task. In particular, we develop a class of embedded-particle models to describe the computational strategies implemented by particular CAs. To do this, we use the computational mechanics framework of Crutchfield and Hanson, in which a CA's information processing is described in terms of regular domains, embedded particles, and their interactions. We then evaluate this class of models by comparing their computational performance to that of the CAs they model. The results demonstrate, via a generally close quantitative agreement between the CAs and the embedded particle models, that this new model class captures the significant functional features in the CAs' space-time behavior that underlie the CAs' computational capability and evolutionary fitness.
Reference: In A. E. Eiben, T. Bäck, M. Schoenauer, and H.-P. Schwefel (eds.), Parallel Problem Solving from Nature-V, 613-622, Springer-Verlag, 1998. SFI working paper: 98-04-034 LANL archive: Abstract: We introduce a class of embedded-particle models for describing the emergent computational strategies observed in cellular automata (CAs) that were evolved for performing certain computational tasks. The models are evaluated by comparing their estimated performances with the actual performances of the CAs they model. The results show, via a close quantitative agreement, that the embedded-particle framework captures the main information processing mechanisms of the emergent computation that arise in these evolved CAs.
Voltar 2.2) SoftwaresFonte: http://ourworld.compuserve.com/homepages/cdosborn/ -> Self Reproducing Cellular Automata Loops ( Site com programa que faz simulação em Java de Automatos Celulares) Fonte: http://www.fourmilab.ch/cellab/ Fonte: http://math.hws.edu/xJava/CA/ -> Possui uma breve introdução sobre automatos celulares e depois passa a falar sobre programas computacionais em Java. Directory: pub -> docs -> vonzuben pub -> Asilomar Conference on Circuits, Systems & Computers, Pacific Grove, ca, November 1978, pp. 55 58 pub -> Forthcoming meetings and conferences pub -> Harmonised compatibility and sharing conditions for video pmse in the 7 9 ghz frequency band, taking into account radar use docs -> A dragon in the tube vonzuben -> Revisão Bibliográfica: Learning Vector Quantization 28/04/2003 vonzuben -> Revisão bibliográfica redes neurais recorrentes docs -> Updated March 2017 Registration Quick Reference Card for Employees/Associates Download 445.54 Kb. Share with your friends:
|