Complexity 

About: Complexity is an academic journal published by Hindawi Publishing Corporation. The journal publishes majorly in the area(s): Computer science & Control theory. It has an ISSN identifier of 1076-2787. It is also open access. Over the lifetime, 6520 publications have been published receiving 74957 citations.

Agent-based computational models and generative social science

Abstract: This article argues that the agent-based computational model permits a distinctive approach to social science for which the term “generative” is suitable. In defending this terminology, features distinguishing the approach from both “inductive” and “deductive” science are given. Then, the following specific contributions to social science are discussed: The agent-based computational model is a new tool for empirical research. It offers a natural environment for the study of connectionist phenomena in social science. Agent-based modeling provides a powerful way to address certain enduring—and especially interdisciplinary—questions. It allows one to subject certain core theories—such as neoclassical microeconomics—to important types of stress (e.g., the effect of evolving preferences). It permits one to study how rules of individual behavior give rise—or “map up”—to macroscopic regularities and organizations. In turn, one can employ laboratory behavioral research findings to select among competing agent-based (“bottom up”) models. The agent-based approach may well have the important effect of decoupling individual rationality from macroscopic equilibrium and of separating decision science from social science more generally. Agent-based modeling offers powerful new forms of hybrid theoretical-computational work; these are particularly relevant to the study of non-equilibrium systems. The agentbased approach invites the interpretation of society as a distributed computational device, and in turn the interpretation of social dynamics as a type of computation. This interpretation raises important foundational issues in social science—some related to intractability, and some to undecidability proper. Finally, since “emergence” figures prominently in this literature, I take up the connection between agent-based modeling and classical emergentism, criticizing the latter and arguing that the two are incompatible. ! 1999 John Wiley & Sons, Inc.

Evolutionary robotics: The biology, intelligence, and technology of self‐organizing machines

Abstract: Let's read! We will often find out this sentence everywhere. When still being a kid, mom used to order us to always read, so did the teacher. Some books are fully read in a week and we need the obligation to support reading. What about now? Do you still love reading? Is reading only for you who have obligation? Absolutely not! We here offer you a new book enPDFd evolutionary robotics the biology intelligence and technology of self organizing machines intelligent robotics and autonomous agents series to read.

Advancing the art of simulation in the social sciences

Abstract: Advancing the state of the art of simulation in the social sciences requires appreciating the unique value of simulation as a third way of doing science, in contrast to both induction and deduction. This essay offers advice for doing simulation research, focusing on the programming of a simulation model, analyzing the results and sharing the results with others. Replicating other people’s simulations gets special emphasis, with examples of the procedures and difficulties involved in the process of replication. Finally, suggestions are offered for building of a community of social scientists who do simulation.

The re-emergence of “emergence”: A venerable concept in search of a theory

Abstract: Despite its current popularity, “emergence” is a concept with a venerable history and an elusive, ambiguous standing in contemporary evolutionary theory. This paper briefly recounts the history of the term and details some of its current usages. Not only are there radically varying interpretations about what emergence means but “reductionist” and “holistic” theorists have very different views about the issue of causation. However, these two seemingly polar positions are not irreconcilable. Reductionism, or detailed analysis of the parts and their interactions, is essential for answering the “how” question in evolution -how does a complex living system work? But holism is equally necessary for answering the “why” question -why did a particular arrangement of parts evolve? In order to answer the “why” question, a broader, multi-leveled paradigm is required. The reductionist approach to explaining emergent complexity has entailed a search for underlying “laws of emergence.” Another alternative is the “Synergism Hypothesis,” which focuses on the “economics” – the functional effects produced by emergent wholes and their selective consequences. This theory, in a nutshell, proposes that the synergistic (co-operative) effects produced by various combinations of parts have played a major causal role in the evolution of biological complexity. It will also be argued that emergent phenomena represent, in effect, a subset of a much larger universe of combined effects in the natural world; there are many different kinds of synergy, but not all synergies represent emergent phenomena.