Memory Evolutive Systems; Hierarchy, Emergence, Cognition provides comprehensive and comprehensible coverage of Memory Evolutive Systems (MEM). Written by the developers of the MEM, the book proposes a mathematical model for autonomous evolutionary systems based on the Category Theory of mathematics. It describes a framework to study and possibly simulate the structure of living systems and their dynamic behavior. This book contributes to understanding the multidisciplinary interfaces between mathematics, cognition, consciousness, biology and the study of complexity. It is organized into three parts. Part A deals with hierarchy and emergence and covers such topics as net of interactions and categories; the binding problem; and complexifications and emergence. Part B is about MEM while Part C discusses MEM applications to cognition and consciousness. The book explores the characteristics of a complex evolutionary system, its differences from inanimate physical systems, and its functioning and evolution in time, from its birth to its death. This book is an ideal reference for researchers, teachers and students in pure mathematics, computer science, cognitive science, study of complexity and systems theory, Category Theory, biological systems theory, and consciousness theory. It would also be of interest to both individuals and institutional libraries.
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Memory Evolutive Systems; Hierarchy, Emergence, Cognition provides comprehensive and comprehensible coverage of Memory Evolutive Systems (MEM). Written by the developers of the MEM, the book proposes a mathematical model for autonomous evolutionary systems based on the Category Theory of mathematics. It describes a framework to study and possibly simulate the structure of living systems and their dynamic behavior.
This book contributes to understanding the multidisciplinary interfaces between mathematics, cognition, consciousness, biology and the study of complexity. It is organized into three parts. Part A deals with hierarchy and emergence and covers such topics as net of interactions and categories; the binding problem; and complexifications and emergence. Part B is about MEM while Part C discusses MEM applications to cognition and consciousness. The book explores the characteristics of a complex evolutionary system, its differences from inanimate physical systems, and its functioning and evolution in time, from its birth to its death.
This book is an ideal reference for researchers, teachers and students in pure mathematics, computer science, cognitive science, study of complexity and systems theory, Category Theory, biological systems theory, and consciousness theory. It would also be of interest to both individuals and institutional libraries.
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) with a differential access to a central hierarchical 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 structure 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. This book provides comprehensive and comprehensible coverage of Memory Evolutive System. It is written by the developers of the Memory Evolutive Systems. It is designed to explore the common language between sciences.
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