An important part of the science of complexity is the study of emergent properties arising through dynamical processes, in various natural and artificial systems. This book presents multidisciplinary approaches for creating and modeling representations of complex systems, and a variety of methods for extracting emergent structures. Offering bio-complexity examples, the coverage extends to self organization, synchronization, stability and robustness. The contributors include researchers in physics, engineering, biology and chemistry.
Emergence and complexity refer to the appearance of higher-level properties and behaviours of a system that obviously comes from the collective dynamics of that system's components. These properties are not directly deducible from the lower-level motion of that system. Emergent properties are properties of the "whole'' that are not possessed by any of the individual parts making up that whole. Such phenomena exist in various domains and can be described, using complexity concepts and thematic knowledges. This book highlights complexity modelling through dynamical or behavioral systems. The pluridisciplinary purposes, developed along the chapters, are able to design links between a wide-range of fundamental and applicative Sciences. Developing such links - instead of focusing on specific and narrow researches - is characteristic of the Science of Complexity that we try to promote by this contribution.
An important part of the science of complexity is the study of emergent properties arising through dynamical processes, in various natural and artificial systems. This book presents multidisciplinary approaches for creating and modeling representations of complex systems, and a variety of methods for extracting emergent structures. Offering bio-complexity examples, the coverage extends to self organization, synchronization, stability and robustness. The contributors include researchers in physics, engineering, biology and chemistry.
This book constitutes the proceedings of the 15th International Symposium on Algorithmic Game Theory, SAGT 2022, which took place in Colchester, UK, in September 2022. The 31 full papers included in this book were carefully reviewed and selected from 83 submissions. They were organized in topical sections as follows: Auctions, markets and mechanism design; computational aspects in games; congestion and network creation games; data sharing and learning; social choice and stable matchings.
This volume collects a selection of contributions which has been presented at the 23rd Italian Workshop on Neural Networks, the yearly meeting of the Italian Society for Neural Networks (SIREN). The conference was held in Vietri sul Mare, Salerno, Italy during May 23-24, 2013. The annual meeting of SIREN is sponsored by International Neural Network Society (INNS), European Neural Network Society (ENNS) and IEEE Computational Intelligence Society (CIS). The book – as well as the workshop- is organized in two main components, a special session and a group of regular sessions featuring different aspects and point of views of artificial neural networks, artificial and natural intelligence, as well as psychological and cognitive theories for modeling human behaviors and human machine interactions, including Information Communication applications of compelling interest.
This book applies complexity theory to cognitive science, and the result is a transformation of this field. It proposes a biophysical theory of human relations, attempting to expand all its implications (for research and theory). It presents the potential clinical applications of this theory in neuroscience and clinical psychology — a general theory of mind change.
Cognitive Design for Artificial Minds explains the crucial role that human cognition research plays in the design and realization of artificial intelligence systems, illustrating the steps necessary for the design of artificial models of cognition. It bridges the gap between the theoretical, experimental, and technological issues addressed in the context of AI of cognitive inspiration and computational cognitive science. Beginning with an overview of the historical, methodological, and technical issues in the field of cognitively inspired artificial intelligence, Lieto illustrates how the cognitive design approach has an important role to play in the development of intelligent AI technologies and plausible computational models of cognition. Introducing a unique perspective that draws upon Cybernetics and early AI principles, Lieto emphasizes the need for an equivalence between cognitive processes and implemented AI procedures, in order to realize biologically and cognitively inspired artificial minds. He also introduces the Minimal Cognitive Grid, a pragmatic method to rank the different degrees of biological and cognitive accuracy of artificial systems in order to project and predict their explanatory power with respect to the natural systems taken as a source of inspiration. Providing a comprehensive overview of cognitive design principles in constructing artificial minds, this text will be essential reading for students and researchers of artificial intelligence and cognitive science.
This book, the outcome of a workshop meeting within ESM 2006, explores the use of emergent computing and self-organization modeling within various applications of complex systems.
Self-organisation, self-regulation, self-repair and self-maintenance are promising conceptual approaches for dealing with complex distributed interactive software and information-handling systems. Self-organising applications dynamically change their functionality and structure without direct user intervention, responding to changes in requirements and the environment. This is the first book to offer an integrated view of self-organisation technologies applied to distributed systems, particularly focusing on multiagent systems. The editors developed this integrated book with three aims: to explain self-organisation concepts and principles, using clear definitions and a strong theoretical background; to examine how self-organising behaviour can be modelled, analysed and systematically engineered into agent behaviour; and to assess the types of problems that can be solved using self-organising multiagent systems. The book comprises chapters covering all three dimensions, synthesising up-to-date research work and the latest technologies and applications. The book offers dedicated chapters on concepts such as self-organisation, emergence in natural systems, software agents, stigmergy, gossip, cooperation and immune systems. The book then explains how to engineer artificial self-organising software, in particular it examines methodologies and middleware infrastructures. Finally, the book presents diverse applications of self-organising software, such as constraint satisfaction, trust management, image recognition and networking. The book will be of interest to researchers working on emergent phenomena and adaptive systems. It will also be suitable for use as a graduate textbook, with chapter summaries and exercises, and an accompanying website that includes teaching slides, exercise solutions and research project outlines. Self-organisation, self-regulation, self-repair and self-maintenance are promising conceptual approaches for dealing with complex distributed interactive software and information-handling systems. Self-organising applications dynamically change their functionality and structure without direct user intervention, responding to changes in requirements and the environment. This is the first book to offer an integrated view of self-organisation technologies applied to distributed systems, particularly focusing on multiagent systems. The editors developed this integrated book with three aims: to explain self-organisation concepts and principles, using clear definitions and a strong theoretical background; to examine how self-organising behaviour can be modelled, analysed and systematically engineered into agent behaviour; and to assess the types of problems that can be solved using self-organising multiagent systems. The book comprises chapters covering all three dimensions, synthesising up-to-date research work and the latest technologies and applications. The book offers dedicated chapters on concepts such as self-organisation, emergence in natural systems, software agents, stigmergy, gossip, cooperation and immune systems. The book then explains how to engineer artificial self-organising software, in particular it examines methodologies and middleware infrastructures. Finally, the book presents diverse applications of self-organising software, such as constraint satisfaction, trust management, image recognition and networking. The book will be of interest to researchers working on emergent phenomena and adaptive systems. It will also be suitable for use as a graduate textbook, with chapter summaries and exercises, and an accompanying website that includes teaching slides, exercise solutions and research project outlines.
This study adopts the logic of Systems Thinking and Control Systems, presenting a simple but complete theory called the Theory of Combinatory Systems. This new theory is able to describe, interpret, explain, simulate and control collective phenomena and their observable effects. Despite specific differences among these phenomena – many of which are “one way", non-repeatable or reproducible – they can all be described or explained, and thus understood, using the model, as simple as it is general, of combinatory systems; that is, systems formed by collectivities, or populations of non-connected and unorganized individuals of some species, which appear to be directed by an invisible hand that guides the analogous actions of similar individuals in order to produce an emerging collective phenomenon. Combinatory Systems function due to the presence of micro control systems which, operating at the individual level, lead to uniform micro behavior by individuals in order to eliminate the (gap) with respect to the objective that is represented – or revealed – by the global information (macro behavior or effect). The book also examines Combinatory Automata, which represent a powerful tool for simulating the most relevant combinatory systems. In stochastic combinatory automata, when both probabilities and periods of transition of state are agent/time/state sensitive, the probabilistic micro behaviors are conditioned by the macro behavior of the entire system, which makes the micro-macro feedback more evident. The Combinatory Systems Theory: Understanding, Modeling and Simulating Collective Phenomena is composed of four main chapters. Chapter 1 presents the basic ideas behind the theory, which are analysed in some detail. Chapter 2 describes the heuristic models of several relevant combinatory systems observable in different environments. Chapter 3, while not making particular use of sophisticated mathematical and statistical tools, presents the Theory of Combinatory Automata and builds models for simulating the operative logic of combinatory systems. Chapter 4 tries to answer three questions: are combinatory systems “systems” in the true sense of the term? Why is this theory able to explain so many and so varied a number of phenomena, even though it is based on a very simple modus operandi? Are combinatory systems different than complex systems? The book has been written with no prerequisite required to read and understand it, in particular math, statistics and computer knowledge.