Pub Date : 2009-01-02DOI: 10.1007/978-3-642-01284-6_15
Hiroki Sayama, Craig B. Laramee
{"title":"Generative Network Automata: A Generalized Framework for Modeling Adaptive Network Dynamics Using Graph Rewritings","authors":"Hiroki Sayama, Craig B. Laramee","doi":"10.1007/978-3-642-01284-6_15","DOIUrl":"https://doi.org/10.1007/978-3-642-01284-6_15","url":null,"abstract":"","PeriodicalId":139082,"journal":{"name":"arXiv: Adaptation and Self-Organizing Systems","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115863588","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Psychological and social systems provide us with a natural domain for the study of anticipations because these systems are based on and operate in terms of intentionality. Psychological systems can be expected to contain a model of themselves and their environments; social systems can be strongly anticipatory and therefore co-construct their environments, for example, in techno-economic (co-)evolutions. Using Dubois' hyper-incursive and incursive formulations of the logistic equation, these two types of systems and their couplings can be simulated. In addition to their structural coupling, psychological and social systems are also coupled by providing meaning reflexively to each other's meaning-processing. Luhmann's distinctions among (1) interactions between intentions at the micro-level, (2) organization at the meso-level, and (3) self-organization of the fluxes of meaningful communication at the global level can be modeled and simulated using three hyper-incursive equations. The global level of self-organizing interactions among fluxes of communication is retained at the meso-level of organization. In a knowledge-based economy, these two levels of anticipatory structuration can be expected to propel each other at the supra-individual level.
{"title":"The communication of meaning in anticipatory systems: a simulation study of the dynamics of intentionality in social interactions","authors":"L. Leydesdorff","doi":"10.1063/1.3020674","DOIUrl":"https://doi.org/10.1063/1.3020674","url":null,"abstract":"Psychological and social systems provide us with a natural domain for the study of anticipations because these systems are based on and operate in terms of intentionality. Psychological systems can be expected to contain a model of themselves and their environments; social systems can be strongly anticipatory and therefore co-construct their environments, for example, in techno-economic (co-)evolutions. Using Dubois' hyper-incursive and incursive formulations of the logistic equation, these two types of systems and their couplings can be simulated. In addition to their structural coupling, psychological and social systems are also coupled by providing meaning reflexively to each other's meaning-processing. Luhmann's distinctions among (1) interactions between intentions at the micro-level, (2) organization at the meso-level, and (3) self-organization of the fluxes of meaningful communication at the global level can be modeled and simulated using three hyper-incursive equations. The global level of self-organizing interactions among fluxes of communication is retained at the meso-level of organization. In a knowledge-based economy, these two levels of anticipatory structuration can be expected to propel each other at the supra-individual level.","PeriodicalId":139082,"journal":{"name":"arXiv: Adaptation and Self-Organizing Systems","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127233587","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We propose an entropic geometrical model of psycho-physical crowd dynamics (with dissipative crowd kinematics), using Feynman action-amplitude formalism that operates on three synergetic levels: macro, meso and micro. The intent is to explain the dynamics of crowds simultaneously and consistently across these three levels, in order to characterize their geometrical properties particularly with respect to behavior regimes and the state changes between them. Its most natural statistical descriptor is crowd entropy $S$ that satisfies the Prigogine's extended second law of thermodynamics, $partial_tSgeq 0$ (for any nonisolated multi-component system). Qualitative similarities and superpositions between individual and crowd configuration manifolds motivate our claim that goal-directed crowd movement operates under entropy conservation, $partial_tS = 0$, while natural crowd dynamics operates under (monotonically) increasing entropy function, $partial_tS > 0$. Between these two distinct topological phases lies a phase transition with a chaotic inter-phase. Both inertial crowd dynamics and its dissipative kinematics represent diffusion processes on the crowd manifold governed by the Ricci flow, with the associated Perelman entropy-action. Keywords: Crowd psycho-physical dynamics, action-amplitude formalism, crowd manifold, Ricci flow, Perelman entropy, topological phase transition
{"title":"Entropic Geometry of Crowd Dynamics","authors":"V. Ivancevic, D. Reid","doi":"10.5772/6951","DOIUrl":"https://doi.org/10.5772/6951","url":null,"abstract":"We propose an entropic geometrical model of psycho-physical crowd dynamics (with dissipative crowd kinematics), using Feynman action-amplitude formalism that operates on three synergetic levels: macro, meso and micro. The intent is to explain the dynamics of crowds simultaneously and consistently across these three levels, in order to characterize their geometrical properties particularly with respect to behavior regimes and the state changes between them. Its most natural statistical descriptor is crowd entropy $S$ that satisfies the Prigogine's extended second law of thermodynamics, $partial_tSgeq 0$ (for any nonisolated multi-component system). Qualitative similarities and superpositions between individual and crowd configuration manifolds motivate our claim that goal-directed crowd movement operates under entropy conservation, $partial_tS = 0$, while natural crowd dynamics operates under (monotonically) increasing entropy function, $partial_tS > 0$. Between these two distinct topological phases lies a phase transition with a chaotic inter-phase. Both inertial crowd dynamics and its dissipative kinematics represent diffusion processes on the crowd manifold governed by the Ricci flow, with the associated Perelman entropy-action. \u0000Keywords: Crowd psycho-physical dynamics, action-amplitude formalism, crowd manifold, Ricci flow, Perelman entropy, topological phase transition","PeriodicalId":139082,"journal":{"name":"arXiv: Adaptation and Self-Organizing Systems","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114688631","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-05-06DOI: 10.4018/978-1-59904-717-1.CH004
R. Standish
The term {em complexity} is used informally both as a quality and as a quantity. As a quality, complexity has something to do with our ability to understand a system or object -- we understand simple systems, but not complex ones. On another level, {em complexity} is used as a quantity, when we talk about something being more complicated than another. In this chapter, we explore the formalisation of both meanings of complexity, which happened during the latter half of the twentieth century.
{"title":"Concept and Definition of Complexity","authors":"R. Standish","doi":"10.4018/978-1-59904-717-1.CH004","DOIUrl":"https://doi.org/10.4018/978-1-59904-717-1.CH004","url":null,"abstract":"The term {em complexity} is used informally both as a quality and as a quantity. As a quality, complexity has something to do with our ability to understand a system or object -- we understand simple systems, but not complex ones. On another level, {em complexity} is used as a quantity, when we talk about something being more complicated than another. \u0000In this chapter, we explore the formalisation of both meanings of complexity, which happened during the latter half of the twentieth century.","PeriodicalId":139082,"journal":{"name":"arXiv: Adaptation and Self-Organizing Systems","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124060498","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2007-08-30DOI: 10.1007/978-3-540-73849-7_4
E. Lozneanu, M. Sanduloviciu
{"title":"Cell-like space charge configurations formed by self-organization in laboratory","authors":"E. Lozneanu, M. Sanduloviciu","doi":"10.1007/978-3-540-73849-7_4","DOIUrl":"https://doi.org/10.1007/978-3-540-73849-7_4","url":null,"abstract":"","PeriodicalId":139082,"journal":{"name":"arXiv: Adaptation and Self-Organizing Systems","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126383849","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We determine the average number $ vartheta (N, K) $, of textit{NK}-Kauffman networks that give rise to the same binary function. We show that, for $ N gg 1 $, there exists a connectivity critical value $ K_c $ such that $ vartheta(N,K) approx e^{phi N} $ ($ phi > 0 $) for $ K K_c $. We find that $ K_c $ is not a constant, but scales very slowly with $ N $, as $ K_c approx log_2 log_2 (2N / ln 2) $. The problem of genetic robustness emerges as a statistical property of the ensemble of textit{NK}-Kauffman networks and impose tight constraints in the average number of epistatic interactions that the genotype-phenotype map can have.
{"title":"The Number of Different Binary Functions Generated by NK-Kauffman Networks and the Emergence of Genetic Robustness","authors":"D. Romero, F. Zertuche","doi":"10.1063/1.2768747","DOIUrl":"https://doi.org/10.1063/1.2768747","url":null,"abstract":"We determine the average number $ vartheta (N, K) $, of textit{NK}-Kauffman networks that give rise to the same binary function. We show that, for $ N gg 1 $, there exists a connectivity critical value $ K_c $ such that $ vartheta(N,K) approx e^{phi N} $ ($ phi > 0 $) for $ K K_c $. We find that $ K_c $ is not a constant, but scales very slowly with $ N $, as $ K_c approx log_2 log_2 (2N / ln 2) $. The problem of genetic robustness emerges as a statistical property of the ensemble of textit{NK}-Kauffman networks and impose tight constraints in the average number of epistatic interactions that the genotype-phenotype map can have.","PeriodicalId":139082,"journal":{"name":"arXiv: Adaptation and Self-Organizing Systems","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124105910","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2007-06-04DOI: 10.1007/978-3-642-02199-2_3
M. Cotsaftis
{"title":"What Makes a System Complex? - An Approach to Self Organization and Emergence","authors":"M. Cotsaftis","doi":"10.1007/978-3-642-02199-2_3","DOIUrl":"https://doi.org/10.1007/978-3-642-02199-2_3","url":null,"abstract":"","PeriodicalId":139082,"journal":{"name":"arXiv: Adaptation and Self-Organizing Systems","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123555977","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2006-06-08DOI: 10.1007/978-3-540-85081-6_3
V. Korotkikh, G. Korotkikh
{"title":"On an irreducible theory of complex systems","authors":"V. Korotkikh, G. Korotkikh","doi":"10.1007/978-3-540-85081-6_3","DOIUrl":"https://doi.org/10.1007/978-3-540-85081-6_3","url":null,"abstract":"","PeriodicalId":139082,"journal":{"name":"arXiv: Adaptation and Self-Organizing Systems","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129861810","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2004-05-06DOI: 10.7551/mitpress/1429.003.0074
Alan N. Hampton, C. Adami
We present the first evolved solutions to a computational task within the Neuronal Organism Evolution model (Norgev) of artificial neural network development. These networks display a remarkable robustness to external noise sources, and can regrow to functionality when severely damaged. In this framework, we evolved a doubling of network functionality (double-NAND circuit). The network structure of these evolved solutions does not follow the logic of human coding, and instead more resembles the decentralized dendritic connection pattern of more biological networks such as the 'C. elegans' brain.
{"title":"Evolution of Robust Developmental Neural Networks","authors":"Alan N. Hampton, C. Adami","doi":"10.7551/mitpress/1429.003.0074","DOIUrl":"https://doi.org/10.7551/mitpress/1429.003.0074","url":null,"abstract":"We present the first evolved solutions to a computational task within the Neuronal Organism Evolution model (Norgev) of artificial neural network development. These networks display a remarkable robustness to external noise sources, and can regrow to functionality when severely damaged. In this framework, we evolved a doubling of network functionality (double-NAND circuit). The network structure of these evolved solutions does not follow the logic of human coding, and instead more resembles the decentralized dendritic connection pattern of more biological networks such as the 'C. elegans' brain.","PeriodicalId":139082,"journal":{"name":"arXiv: Adaptation and Self-Organizing Systems","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133454855","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2004-04-06DOI: 10.7551/mitpress/1429.003.0060
R. Standish
Ecolab and Webworld are both models of evolution produced by adding evolution to ecological equations. They differ primarily in the form of the ecological equations. Both models are self-organised to a state where extinctions balance speciations. However, Ecolab shows evidence of this self-organised state being critical, whereas Webworld does not. This paper examines the self-organised states of these two models and suggest the likely cause of the difference. Also the lifetime distribution for a mean field version of Ecolab is computed, showing that the fat tail of the distribution is due to coevolutionary adaption of the species.
{"title":"Ecolab, Webworld and self-organisation","authors":"R. Standish","doi":"10.7551/mitpress/1429.003.0060","DOIUrl":"https://doi.org/10.7551/mitpress/1429.003.0060","url":null,"abstract":"Ecolab and Webworld are both models of evolution produced by adding evolution to ecological equations. They differ primarily in the form of the ecological equations. Both models are self-organised to a state where extinctions balance speciations. However, Ecolab shows evidence of this self-organised state being critical, whereas Webworld does not. This paper examines the self-organised states of these two models and suggest the likely cause of the difference. Also the lifetime distribution for a mean field version of Ecolab is computed, showing that the fat tail of the distribution is due to coevolutionary adaption of the species.","PeriodicalId":139082,"journal":{"name":"arXiv: Adaptation and Self-Organizing Systems","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122571590","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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