Open Access
What are agent-based models?
Nigel Gilbert
- 01 Jun 2008
474
TL;DR: This chapter discusses designing and Developing Agent-Based Models, and building the Collectivities Model Step by Step, as well as reporting on advances in agent-Based Modeling.
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Abstract: Series Editor's Introduction Preface Acknowledgments 1. The Idea of Agent-Based Modeling 1.1 Agent-Based Modeling 1.2 Some Examples 1.3 The Features of Agent-Based Modeling 1.4 Other Related Modeling Approaches 2. Agents, Environments, and Timescales 2.1 Agents 2.2 Environments 2.3 Randomness 2.4 Time 3. Using Agent-Based Models in Social Science Research 3.1 An Example of Developing an Agent-Based Model 3.2 Verification: Getting Rid of the Bugs 3.3 Validation 3.4 Techniques for Validation 3.5 Summary 4. Designing and Developing Agent-Based Models 4.1 Modeling Toolkits, Libraries, Languages, Frameworks, and Environments 4.2 Using NetLogo to Build Models 4.3 Building the Collectivities Model Step by Step 4.4 Planning an Agent-Based Model Project 4.5 Reporting Agent-Based Model Research 4.6 Summary 5. Advances in Agent-Based Modeling 5.1 Geographical Information Systems 5.2 Learning 5.3 Simulating Language Resources Glossary References Index About the Author
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Citations
•Journal Article
Handbook of Computational Economics
TL;DR: This paper presents a meta-modelling framework for general equilibrium modelling for policy analysis and forecasting of dynamic linear economies and some of the methods used in this framework came from previous work on dynamic dynamic programming in economics.
Agribusiness supply chain risk management: A review of quantitative decision models
TL;DR: In this paper, the authors identify robustness and resilience as two key techniques for managing risk in agricultural supply chains and propose clear definitions and metrics for these terms; they then use these definitions to classify the agricultural supply chain risk management literature.
The life course cube: A tool for studying lives
TL;DR: The ‘life course cube’ is introduced, which graphically defines and illustrates time-domain-level interdependencies and their multiple interactions that are central to understanding life courses.
333
Agent-Based Modeling
Dirk Helbing
- 10 Feb 2012
TL;DR: Since the advent of computers, the natural and engineering sciences have enormously progressed and it would be very surprising, if computers could not make a contribution to a better understanding of social and economic systems.
309
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.
281
References
Intelligent Agents: Theory and Practice
TL;DR: Agent theory is concerned with the question of what an agent is, and the use of mathematical formalisms for representing and reasoning about the properties of agents as discussed by the authors ; agent architectures can be thought of as software engineering models of agents; and agent languages are software systems for programming and experimenting with agents.
Dynamic models of segregation
TL;DR: The systemic effects are found to be overwhelming: there is no simple correspondence of individual incentive to collective results, and a general theory of ‘tipping’ begins to emerge.
5.1K
•Journal Article
Intelligent Agents: Theory and Practice
TL;DR: The aim in this paper is to point the reader at what they perceive to be the most important theoretical and practical issues associated with the design and construction of intelligent agents.
4.3K
Multi-Agent Systems for the Simulation of Land-Use and Land-Cover Change: A Review
TL;DR: In this paper, an overview of multi-agent system models of land-use/cover change (MAS/LUCC) is presented, which combine a cellular landscape model with agent-based representations of decisionmaking, integrating the two components through specification of interdependencies and feedbacks between agents and their environment.
2K
FROM FACTORS TO ACTORS: Computational Sociology and Agent-Based Modeling
Michael W. Macy,Robert Willer +1 more
TL;DR: Agent-based models (ABMs) as mentioned in this paper have been widely used in computational sociology to model social life as interactions among adaptive agents who influence one another in response to the influence they receive, such as diffusion of information, emergence of norms, coordination of conventions or participation in collective action.
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