Self-organization, emergence and the architecture of complexity

2007

Men in their arrogance claim to understand the nature of Creation, and devise elaborate theories to describe its behaviour. But always they discover in the end that God is more clever than they thought Sister Miriam Godwinson The fast changing reality in technical and natural domains perceived by always more accurate observations has drawn the attention on a new and very broad class of systems mainly characterized by specific behaviour which has been entered under the common wording "complexity". Based on elementary system graph representation with components as nodes and interactions as vertices, it is shown that systems belong to only three states : simple, complicated, and complex, the main properties of which are discussed. The first two states have been studied at length over past centuries, and the last one finds its origin in the elementary fact that when system performance is pushed up, there exists a threshold above which interaction between components overtake outside interaction. At the same time, system self-organizes and filters corresponding outer action, making it more robust to outer effect, with emergence of a new behaviour which was not predictable from only components study. Examples in Physics and Biology are given, and three main classes of "complexity" behaviour are distinguished corresponding to different levels of difficulty to handle the problem of their dynamics. The great interest of using complex state properties in man-made systems is stressed and important issues are discussed. They mainly concentrate on the difficult balance to be established between the relative system isolation when becoming complex and the delegation of corresponding new capability from (outside) operator. This implies giving the system some "intelligence" in an adequate frame between the new augmented system state and supervising operator, with consequences on the canonical system triplet {effector-sensor-controller} which has to be reorganized in this new setting. Moreover, it is observed that entering complexity state opens the possibility for the function to feedback onto the structure, ie to mimic at technical level the invention of Nature over Her very long history.

Synthese, 2012

Philosophical accounts of emergence have been explicated in terms of logical relationships between statements (derivation) or static properties (function and realization). Jaegwon Kim is a modern proponent. A property is emergent if it is not explainable by (or reducible to) the properties of lower level components. This approach, I will argue, is unable to make sense of the kinds of emergence that are widespread in scientific explanations of complex systems. The standard philosophical notion of emergence posits the wrong dichotomies, confuses compositional physicalism with explanatory physicalism, and is unable to represent the type of dynamic processes (self-organizing feedback) that both generate emergent properties and express downward causation. Keywords Emergence • Downward causation • Reduction • Self-organization • Chaos • Feedback 1 A better translation is "the whole is over and above its parts, and not just the sum of them all."

2008

All rights reserved. No part of this publication may be reproduced, stored on a retrieval system, or transmitted, in any form or by any means, electronic, mechanical , photocopying, micro! lming, recording or otherwise, without written permission from the publisher. Credits Thanks goes to the following for help in obtaining original texts, and/or for per-editors have supplied the title, noting that he " almost certainly " used the manuscript for a January 1884 lecture on " Design and Chance. " See S&'.'()D %4 +C5&$-D <A :-'&8-K 7 +C&%(%$%)'85$ !;'. D oes nature resemble a ramp or a ladder? Are nature's ubiquitous dis-continuities merely apparent differences, fully reducible to quantitative differences, or do they signal qualitative ruptures that cannot be understood to be the smooth accumulation of simple accretions or growth? Are qualitative differences merely illusory, fully explicable once we capture the laws of the deepest level of ...

Computer and Information Sciences, …, 2006

1994

I seek to define rigorously the concept of an emergent phenomenon in a complex system, together with its implications for explanation, understanding and prediction in such systems. I argue that in a certain fundamental sense, emergent systems are those in which even perfect knowledge and understanding may give us no predictive information. In them the optimal means of prediction is simulation. I investigate the consequences of this for certain decidability and complexity issues, and then explain why these limitations do not preclude all means of doing interesting science in such systems. I touch upon some recent incorporation of this work into the investigation of self-organised criticalities.

Proceedings - Academy of Management, 2016

Arxiv preprint nlin/0101006, 2001

Numerous definitions for complexity have been proposed over the last half century, with little consensus achieved on how to use the term. A definition of complexity is supplied here that is closely related to the Kolmogorov Complexity and Shannon Entropy measures widely used as complexity measures, yet addresses a number of concerns raised against these measures. However, the price of doing this is to introduce context dependence into the definition of complexity. It is argued that such context dependence is an inherent property of complexity, and related concepts such as entropy and emergence. Scientists are uncomfortable with such context dependence, which smacks of subjectivity, and this is perhaps the reason why little agreement has been found on the meaning of these terms.

2010

Abstract While some branches of complexity theory are advancing rapidly, the same cannot be said for our understanding of emergence. Despite a complete knowledge of the rules underlying the interactions between the parts of many systems, we are often baffled by their sudden transitions from simple to complex. Here I propose a solution to this conceptual problem.

Complexity, 2009

Complex Systems Science aims to understand concepts like complexity, self-organization, emergence and adaptation, among others. The inherent fuzziness in complex systems definitions is complicated by the unclear relation among these central processes: does self-organisation emerge or does it set the preconditions for emergence? Does complexity arise by adaptation or is complexity necessary for adaptation to arise? The inevitable consequence of the current impasse is miscommunication among scientists within and across disciplines. We propose a set of concepts, together with their possible information-theoretic interpretations, which can be used to facilitate the Complex Systems Science discourse. Our hope is that the suggested information-theoretic baseline may promote consistent communications among practitioners, and provide new insights into the field. This does not limit evolution to DNA/RNA based terrestrial biology-see Section 6.

cs.calstatela.edu