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An Introduction to Transfer Entropy
  • Language: en
  • Pages: 210

An Introduction to Transfer Entropy

  • Type: Book
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  • Published: 2016-11-15
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  • Publisher: Springer

This book considers a relatively new metric in complex systems, transfer entropy, derived from a series of measurements, usually a time series. After a qualitative introduction and a chapter that explains the key ideas from statistics required to understand the text, the authors then present information theory and transfer entropy in depth. A key feature of the approach is the authors' work to show the relationship between information flow and complexity. The later chapters demonstrate information transfer in canonical systems, and applications, for example in neuroscience and in finance. The book will be of value to advanced undergraduate and graduate students and researchers in the areas of computer science, neuroscience, physics, and engineering.

The Local Information Dynamics of Distributed Computation in Complex Systems
  • Language: en
  • Pages: 249

The Local Information Dynamics of Distributed Computation in Complex Systems

The nature of distributed computation in complex systems has often been described in terms of memory, communication and processing. This thesis presents a complete information-theoretic framework to quantify these operations on information (i.e. information storage, transfer and modification), and in particular their dynamics in space and time. The framework is applied to cellular automata, and delivers important insights into the fundamental nature of distributed computation and the dynamics of complex systems (e.g. that gliders are dominant information transfer agents). Applications to several important network models, including random Boolean networks, suggest that the capability for information storage and coherent transfer are maximised near the critical regime in certain order-chaos phase transitions. Further applications to study and design information structure in the contexts of computational neuroscience and guided self-organisation underline the practical utility of the techniques presented here.

Guided Self-Organization: Inception
  • Language: en
  • Pages: 488

Guided Self-Organization: Inception

Is it possible to guide the process of self-organisation towards specific patterns and outcomes? Wouldn’t this be self-contradictory? After all, a self-organising process assumes a transition into a more organised form, or towards a more structured functionality, in the absence of centralised control. Then how can we place the guiding elements so that they do not override rich choices potentially discoverable by an uncontrolled process? This book presents different approaches to resolving this paradox. In doing so, the presented studies address a broad range of phenomena, ranging from autopoietic systems to morphological computation, and from small-world networks to information cascades in...

Information Dynamics
  • Language: en
  • Pages: 362

Information Dynamics

Proceedings of a NATO ASI held in Irsee/Kaufbeuren, Germany, June 15--26, 1990

Information Decomposition of Target Effects from Multi-Source Interactions
  • Language: en
  • Pages: 337

Information Decomposition of Target Effects from Multi-Source Interactions

  • Type: Book
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  • Published: 2018-09-04
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  • Publisher: MDPI

This book is a printed edition of the Special Issue "Information Decomposition of Target Effects from Multi-Source Interactions" that was published in Entropy

Complexity, Criticality and Computation (C³)
  • Language: en
  • Pages: 269

Complexity, Criticality and Computation (C³)

  • Type: Book
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  • Published: 2018-04-06
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  • Publisher: MDPI

This book is a printed edition of the Special Issue "Complexity, Criticality and Computation (C³)" that was published in Entropy

Information-based methods for neuroimaging: analyzing structure, function and dynamics
  • Language: en
  • Pages: 192

Information-based methods for neuroimaging: analyzing structure, function and dynamics

The aim of this Research Topic is to discuss the state of the art on the use of Information-based methods in the analysis of neuroimaging data. Information-based methods, typically built as extensions of the Shannon Entropy, are at the basis of model-free approaches which, being based on probability distributions rather than on specific expectations, can account for all possible non-linearities present in the data in a model-independent fashion. Mutual Information-like methods can also be applied on interacting dynamical variables described by time-series, thus addressing the uncertainty reduction (or information) in one variable by conditioning on another set of variables. In the last years...

Progress in Artificial Life
  • Language: en
  • Pages: 413

Progress in Artificial Life

  • Type: Book
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  • Published: 2007-11-06
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  • Publisher: Springer

This book constitutes the refereed proceedings of the Third Australian Conference on Artificial Life, ACAL 2007, held in Gold Coast, Australia, in December 2007. The 34 revised full papers presented were carefully reviewed and selected from 70 submissions. Research in Alife covers the main areas of biological behaviour as a metaphor for computational models, computational models that reproduce/duplicate a biological behaviour, and computational models to solve biological problems.

Transfer Entropy
  • Language: en
  • Pages: 335

Transfer Entropy

  • Type: Book
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  • Published: 2018-08-24
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  • Publisher: MDPI

This book is a printed edition of the Special Issue "Transfer Entropy" that was published in Entropy

Advances in Artificial Life
  • Language: en
  • Pages: 520

Advances in Artificial Life

The two-volume set LNAI 5777 and LNAI 5778 constitutes the thoroughly refereed post-conference proceedings of the 10th European Conference, ECAl 2009, held in Budapest, Hungary, in September 2009. The 141 revised full papers presented were carefully reviewed and selected from161 submissions. The papers are organized in topical sections on evolutionary developmental biology and hardware, evolutionary robotics, protocells and prebiotic chemistry, systems biology, artificial chemistry and neuroscience, group selection, ecosystems and evolution, algorithms and evolutionary computation, philosophy and arts, optimization, action, and agent connectivity, and swarm intelligence.