Open Access
What are agent-based models?
TLDR
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.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 Authorread more
Citations
More filters
Journal ArticleDOI
Rational choice theory
TL;DR: The main purpose of rational choice theory is to explain social phenomena by assuming rational choice at the actor's level as discussed by the authors, and the theory assumes two mechanisms: choice by actors and the macro-micro-macro transition.
Book ChapterDOI
Agent-Based Modeling
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.
Journal ArticleDOI
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.
Book ChapterDOI
Introduction to Agent-Based Modelling
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.
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.
References
More filters
Journal ArticleDOI
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.
Journal ArticleDOI
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.
Journal ArticleDOI
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.
Journal ArticleDOI
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.
Journal ArticleDOI
Rationality in Psychology and Economics
TL;DR: The authors compare and contrast the concepts of rationality that are prevalent in psychology and economics, respectively, and conclude that economics has almost uniformly treated human behavior as rational and psychology has always been concerned with both the irrational and the rational aspects of behavior.