Brownian Agents and Active Particles: Collective Dynamics in the Natural and Social Sciences (Springer Series in Synergetics)

this Book Lays Out A Vision For A Coherent Framework For Understanding Complex Systems'' (from The Foreword By J. Doyne Farmer). By Developing The Genuine Idea Of Brownian Agents, The Author Combines Concepts From Informatics, Such As Multiagent Systems, With Approaches Of Statistical Many-particle Physics. This Way, An Efficient Method For Computer Simulations Of Complex Systems Is Developed Which Is Also Accessible To Analytical Investigations And Quantitative Predictions. The Book Demonstrates That Brownian Agent Models Can Be Successfully Applied In Many Different Contexts, Ranging From Physicochemical Pattern Formation, To Active Motion And Swarming In Biological Systems, To Self-assembling Of Networks, Evolutionary Optimization, Urban Growth, Economic Agglomeration And Even Social Systems. When we contemplate phenomena as diverse as electrochemical deposition or the spatial patterns of urban development, it is natural to assume that they havenothing incommon. Afterall,therearemanylevelsinthehierarchythat builds up from atoms to human society, and the rules that govern atoms are quite di?erent from those that govern the geographical emergence of a city. The common view among many, if not most, biologists and social scientists is that the devil is entirely in the details. This school of thought asserts that social science and biology have little or nothing in common, and indeed many biologists claim that even di?erent?elds of biology have little in common. If they are right, then science can only proceed by recording vast lists of details that no common principles will ever link together. Physics, in contrast, has achieved a parsimonious description for a broad range of phenomena based on only a few general principles. The phenomena that physics addresses are unquestionably much simpler than those of biology or social science, and on the surface appear entirely dissimilar. A cell is far more complicated than a pendulum or an atom, and human society, being builtoutofagreatmanycells,isfarmorecomplicatedstill. Cellsandsocieties have many layers of hierarchical organization, with complex functional and computational properties; they have identities, idiosyncracies stemming from an accumulation of historical contingency that makes them impossible to characterize in simple mathematical terms. Their complexity is far beyond that of the simple systems usually studied in physics. Front Matter....Pages I-XVI Complex Systems and Agent Models....Pages 1-49 Active Particles....Pages 51-131 Aggregation and Physicochemical Structure Formation....Pages 133-173 Self-Organization of Networks....Pages 175-201 Tracks and Trail Formation in Biological Systems....Pages 203-245 Movement and Trail Formation by Pedestrians....Pages 247-266 Evolutionary Optimization Using Brownian Searchers....Pages 267-293 Analysis and Simulation of Urban Aggregation....Pages 295-333 Economic Agglomeration....Pages 335-355 Spatial Opinion Structures in Social Systems....Pages 357-385 Erratum....Pages e1-e1 Back Matter....Pages 387-420 Lays out a vision for a coherent framework for understanding complex systems. By developing the idea of Brownian agents, this work combines concepts from informatics, such as multiagent systems, with approaches of statistical many-particle physics. It also shows that Brownian agent models can be successfully applied in many different contexts.