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Register a new userCasualty Dynamics in Wars and Terrorism and the Scale-Free Organization of Social Systems
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Authors
Ingo Piepers
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In this paper I propose a mechanism for the explanation of power-law characteristics of casualty dynamics in inter-state wars, intra-state wars and terrorist attacks: the scale-free physical organization of social systems. Other explanations - self-organized criticality (Cederman, 2003) and the redistribution of total attack capabilities (Johnson et al. 2006) - do not provide a consistent framework for the power-law characteristics of casualty dynamics. The development in time of the power-law characteristics of casualty dynamics during wars and conflicts provides clues for the functioning of social systems which are targeted, and/or for the (in)effectiveness and strategies of actors using force (violence) against these social systems.
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Social systems must fulfil four basic functions to ensure their survival in competitive conditions. Social systems must provide for: (1) energy and other necessities of life, (2) security against external and internal threats, (3) identity and self-development, and (4) consistency and direction. These functions result in four more or less autonomous aspect systems; these aspect systems interact. Between the variables of basic functions and variables of aspect systems, a minimal level of consistency is required to facilitate growth and development, and to ensure the (future) survivability of the social system. Sooner or later, growth, change, and differentiated development result in inconsistencies within/between basic functions and aspect systems. These inconsistencies affect the effectiveness and efficiency of these social systems to provide for the basic functions. Periodically, deliberate or spontaneous corrective adjustments of social systems are required, to correct for these inconsistencies.
The Internet is the most complex system ever created in human history. Therefore, its dynamics and traffic unsurprisingly take on a rich variety of complex dynamics, self-organization, and other phenomena that have been researched for years. This paper is a review of the complex dynamics of Internet traffic. Departing from normal treatises, we will take a view from both the network engineering and physics perspectives showing the strengths and weaknesses as well as insights of both. In addition, many less covered phenomena such as traffic oscillations, large-scale effects of worm traffic, and comparisons of the Internet and biological models will be covered.
Self-organization can be broadly defined as the ability of a system to display ordered spatio-temporal patterns solely as the result of the interactions among the system components. Processes of this kind characterize both living and artificial systems, making self-organization a concept that is at the basis of several disciplines, from physics to biology and engineering. Placed at the frontiers between disciplines, Artificial Life (ALife) has heavily borrowed concepts and tools from the study of self-organization, providing mechanistic interpretations of life-like phenomena as well as useful constructivist approaches to artificial system design. Despite its broad usage within ALife, the concept of self-organization has been often excessively stretched or misinterpreted, calling for a clarification that could help with tracing the borders between what can and cannot be considered self-organization. In this review, we discuss the fundamental aspects of self-organization and list the main usages within three primary ALife domains, namely soft (mathematical/computational modeling), hard (physical robots), and wet (chemical/biological systems) ALife. We also provide a classification to locate this research. Finally, we discuss the usefulness of self-organization and related concepts within ALife studies, point to perspectives and challenges for future research, and list open questions. We hope that this work will motivate discussions related to self-organization in ALife and related fields.
We study the consequences of introducing individual nonconformity in social interactions, based on Axelrods model for the dissemination of culture. A constraint on the number of situations in which interaction may take place is introduced in order to lift the unavoidable ho mogeneity present in the final configurations arising in Axelrods related models. The inclusion of this constraint leads to the occurrence of complex patterns of intracultural diversity whose statistical properties and spatial distribution are characterized by means of the concepts of cultural affinity and cultural cli ne. It is found that the relevant quantity that determines the properties of intracultural diversity is given by the fraction of cultural features that characterizes the cultural nonconformity of individuals.
Financial markets display scale-free behavior in many different aspects. The power-law behavior of part of the distribution of individual wealth has been recognized by Pareto as early as the nineteenth century. Heavy-tailed and scale-free behavior of the distribution of returns of different financial assets have been confirmed in a series of works. The existence of a Pareto-like distribution of the wealth of market participants has been connected with the scale-free distribution of trading volumes and price-returns. The origin of the Pareto-like wealth distribution, however, remained obscure. Here we show that it is the process of trading itself that under two mild assumptions spontaneously leads to a self-organization of the market with a Pareto-like wealth distribution for the market participants and at the same time to a scale-free behavior of return fluctuations. These assumptions are (i) everybody trades proportional to his current capacity and (ii) supply and demand determine the relative value of the goods.
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