Memory evolutive systems hierarchy, emergence, cognition. [electronic resource] :

• 其他作者：
  • Charles Ehresmann, Andree.
  • Vanbremeersch, Jean-Paul.
• 其他題名：
  • Studies in multidisciplinarity ;
• 出版： [S.l.] : Elsevier Science
• 叢書名： Studies in multidisciplinarity ;v. 4
• 主題： Self-organizing systems , Self-organizing systems , SCIENCE--System Theory. , Electronic books.
• ISBN： 9780444522443 、 0444522441 、 9780080555416 (electronic bk.) 、 0080555411 (electronic bk.) 、 9786611186807 、 6611186808
• FIND@SFXID: CGU
• 資料類型: 電子書
• 內容註: Includes bibliographical references and index. Part A: Hierarchy. Emergence -- Chapter 1: Net of Interactions and Categories -- Chapter 2: The Binding Problem -- Chapter 3: Hierarchy and Reductionism -- Chapter 4: Complexifications and Emergence -- Part B: Memory Evolutive Systems -- Chapter 5: Evolutionary Systems -- Chapter 6: Internal Organization and MES -- Chapter 7: Robustness and Plasiticity -- Chapter 8: Memory and Learning -- Part C: Application to Cognition and Consciousness -- Chapter 9: Cognitive Systems and MES of CAT-Neurons -- Chapter10: Semantics, Archetypal Core and Consciousness.
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• 摘要註: The theory of Memory Evolutive Systems represents a mathematical model for natural open self-organizing systems, such as biological, sociological or neural systems. In these systems, the dynamics are modulated by the cooperative and/or competitive interactions between the global system and a net of internal Centers of Regulation (CR) wich a differential access to a central heirarchical Memory. The MES proposes a mathematical model for autonomous evolutionary systems and is based on the Category Theory of mathematics. It provides a framework to study and possibly simulate the structre of "living systems" and their dynamic behavior. MES explores what characterizes a complex evolutionary system, what distinguishes it from inanimate physical systems, its functioning and evolution in time, from its birth to its death. The behavior of this type of system depends heavily on its former experiences, and a model representing the system over a period of time, could anticipate later behavior and perhaps even predict some evolutionary alternatives. The role of the MES model will be two-fold: theoretical, for a comprehension of a fundamental nature and practical, for applications in biology, medicine, sociology, ecology, economy, meteorology, and other sciences. Key Features: *Comprehensive and comprehensible coverage of Memory Evolutive System *Written by the developers of the Memory Evolutive Systems *Designed to explore the common language between sciences.
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