Decision Making in Agent-Based Models

AbstractMany agent-based models (ABMs) try to explain large-scale phenomena by reducing them to behaviors at lower scales. At these scales in social systems are functional groups such as households, religious congregations, coops and local governments. The intra-group dynamics of functional groups often generate inefficient or unexpected behavior that cannot be predicted by modeling groups as basic units. We introduce a framework for modeling intra-group decision-making and its interaction with social norms, using the household as our focus. We select phenomena related to women’s empowerment in agriculture as examples influenced by both intra-household dynamics and gender norms. Our framework proves more capable of replicating these phenomena than two common types of ABMs. We conclude that it is not enough to build multi-scale models; explaining social behaviors entails modeling intra-scale dynamics.

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Narrative analysis in economics as climbing complexity

Voprosy Ekonomiki ◽

10.32609/0042-8736-2020-4-5-30 ◽

2020 ◽

pp. 5-30

Author(s):

Vitaly L. Tambovtsev

Keyword(s):

Decision Making ◽

Empirical Research ◽

Narrative Analysis ◽

Agent Based Models ◽

Agent Based ◽

Basic Framework ◽

Feasible Alternative ◽

Effective Instrument

Two turns in economics during last decades are analyzed — complexity turn, and information turn, and the narrative analysis role for these turns realization is discussed. Basic framework of narrative analysis is described, and it is shown that its efficacy is limited by groups of individuals which have resources that give them possibilities to treat the narrative’s plot as a feasible alternative in decision-making situation. It is grounded that now agent-based models are the effective instrument for theoretical and empirical research under turns to complexity or information alike.

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The Boundaries of Cognition and Decision Making

Towards Bayesian Model-Based Demography ◽

10.1007/978-3-030-83039-7_6 ◽

2021 ◽

pp. 93-112

Author(s):

Toby Prike ◽

Philip A. Higham ◽

Jakub Bijak

Keyword(s):

Decision Making ◽

Virtual Reality ◽

Empirical Evidence ◽

Experimental Methodology ◽

Agent Based Models ◽

New Developments ◽

Agent Based ◽

Individual Level ◽

Extended Discussion ◽

Psychological Experiments

AbstractThis chapter outlines the role that individual-level empirical evidence gathered from psychological experiments and surveys can play in informing agent-based models, and the model-based approach more broadly. To begin with, we provide an overview of the way that this empirical evidence can be used to inform agent-based models. Additionally, we provide three detailed exemplars that outline the development and implementation of experiments conducted to inform an agent-based model of asylum migration, as well as how such data can be used. There is also an extended discussion of important considerations and potential limitations when conducting laboratory or online experiments and surveys, followed by a brief introduction to exciting new developments in experimental methodology, such as gamification and virtual reality, that have the potential to address some of these limitations and open the door to promising and potentially very fruitful new avenues of research.

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From individual Fuzzy Cognitive Maps to Agent Based Models: Modeling multi-factorial and multi-stakeholder decision-making for water scarcity

Journal of Environmental Management ◽

10.1016/j.jenvman.2019.109482 ◽

2019 ◽

Vol 250 ◽

pp. 109482 ◽

Cited By ~ 8

Author(s):

Sara Mehryar ◽

Richard Sliuzas ◽

Nina Schwarz ◽

Ali Sharifi ◽

Martin van Maarseveen

Keyword(s):

Decision Making ◽

Water Scarcity ◽

Cognitive Maps ◽

Fuzzy Cognitive Maps ◽

Agent Based Models ◽

Agent Based ◽

Multi Stakeholder

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Agent-Based Modeling Bridges Theory of Behavioral Finance and Financial Markets

Multi-Agent Applications with Evolutionary Computation and Biologically Inspired Technologies ◽

10.4018/978-1-60566-898-7.ch008 ◽

2010 ◽

pp. 134-155

Author(s):

Hiroshi Takahashi ◽

Takao Terano

Keyword(s):

Decision Making ◽

Asset Pricing ◽

Financial Market ◽

Behavioral Finance ◽

Investment Strategy ◽

Agent Based Modeling ◽

Agent Based Models ◽

Agent Based ◽

Micro Level ◽

Fundamental Values

This chapter describes advances of agent-based models to financial market analyses based on our recent research. We have developed several agent-based models to analyze microscopic and macroscopic links between investor behaviors and price fluctuations in a financial market. The models are characterized by the methodology that analyzes the relations among micro-level decision making rules of the agents and macro-level social behaviors via computer simulations. In this chapter, we report the outline of recent results of our analysis. From the extensive analyses, we have found that (1) investors’ overconfidence behaviors plays various roles in a financial market, (2) overconfident investors emerge in a bottom-up fashion in the market, (3) they contribute to the efficient trades in the market, which adequately reflects fundamental values, (4) the passive investment strategy is valid in a realistic efficient market, however, it could have bad influences such as instability of market and inadequate asset pricing deviations, and (5) under certain assumptions, the passive investment strategy and active investment strategy could coexist in a financial market.

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