Book Chapter10.1007/978-90-481-8927-4_7
Agent-Based Modeling and Complexity
Steven M. Manson,Shipeng Sun,Dudley B. Bonsal +2 more
- 01 Jan 2012
- pp 125-139
TL;DR: Some of the key issues found at the interface of complexity research and agent-based modeling are examined: the range of complexity approaches; tensions between theoretical and empirical research; calibration, verification, and validation; scale; equilibrium and change; and decision making.
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Abstract: Complexity theory provides a common language and rubric for applying agent-based processes to a range of complex systems. Agent-based modeling in turn advances complexity science by actuating many complex system characteristics, such as self-organization, nonlinearity, sensitivity, and resilience. There are many points of contact between complexity and agent-based modeling, and we examine several of particular importance: the range of complexity approaches; tensions between theoretical and empirical research; calibration, verification, and validation; scale; equilibrium and change; and decision making. These issues, together and separately, comprise some of the key issues found at the interface of complexity research and agent-based modeling.
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Citations
Cybernetics, or Control and Communication in the Animal and the Machine
TL;DR: In this article, the authors propose a Cybernetics or Control and Communication in the Animal and the Machine (CACM) for controlling and communicating with animals and the machines.
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Introduction to Agent-Based Modelling
Andrew Crooks,Alison J. Heppenstall +1 more
- 01 Jan 2012
TL;DR: This chapter presents in this chapter an overview of ABM; the main features of an agent-based model are given, along with a discussion of what constitutes an agent -based model.
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Simple or complicated agent-based models? A complicated issue
Zhanli Sun,Iris Lorscheid,James D.A. Millington,Steffen Lauf,Nicholas R. Magliocca,Jrgen Groeneveld,Stefano Balbi,Henning Nolzen,Birgit Mller,Jule Schulze,Carsten M. Buchmann +10 more
TL;DR: While ABMs should be constructed as simple as possible but as complicated as necessary to address the predefined research questions, this paper warns modellers of the pitfalls and risks of building mid-level models mixing stylized and empirical components.
A review of urban residential choice models using agent-based modeling
TL;DR: A review of agent-based models of urban residential choices can be found in this article, where the authors focus on three fundamental new features introduced by agents: agent heterogeneity, land market processes, and the method of measuring the extensive model outputs.
149
Agent-based modeling and simulation in archaeology
Gabriel Wurzer,Kerstin Kowarik,Hans Reschreiter +2 more
- 01 Jan 2015
TL;DR: In this paper, an agent-based simulation model for understanding the emergence of Patagonian ethnicity and territoriality is presented, based on the Artificial Anasazi (AA) model.
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Judgment Under Uncertainty: Heuristics and Biases
Amos Tversky,Daniel Kahneman +1 more
- 01 Jan 1974
TL;DR: The authors described three heuristics that are employed in making judgements under uncertainty: representativeness, availability of instances or scenarios, and adjustment from an anchor, which is usually employed in numerical prediction when a relevant value is available.
A logical calculus of the ideas immanent in nervous activity
Warren S. McCulloch,Walter Pitts +1 more
TL;DR: In this article, it is shown that many particular choices among possible neurophysiological assumptions are equivalent, in the sense that for every net behaving under one assumption, there exists another net which behaves under another and gives the same results, although perhaps not in the same time.
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Resilience and Stability of Ecological Systems
TL;DR: The traditional view of natural systems, therefore, might well be less a meaningful reality than a perceptual convenience.
Resilience, Adaptability and Transformability in Social–ecological Systems
TL;DR: The concept of resilience has evolved considerably since Holling's (1973) seminal paper as discussed by the authors and different interpretations of what is meant by resilience, however, cause confusion, and it can be counterproductive to seek definitions that are too narrow.
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