Agent-Based Computational Model

2017 ◽  
Author(s):  
Joshua M. Epstein
Keyword(s):  
Computational Model ◽  
Bounded Rationality ◽  
Time Scales ◽  
Spatially Explicit ◽  
Agent Based ◽  
Affective Component ◽  
Elementary Type ◽  
Social Component ◽  
Different Time Scales

This part describes the agent-based and computational model for Agent_Zero and demonstrates its capacity for generative minimalism. It first explains the replicability of the model before offering an interpretation of the model by imagining a guerilla war like Vietnam, Afghanistan, or Iraq, where events transpire on a 2-D population of contiguous yellow patches. Each patch is occupied by a single stationary indigenous agent, which has two possible states: inactive and active. The discussion then turns to Agent_Zero's affective component and an elementary type of bounded rationality, as well as its social component, with particular emphasis on disposition, action, and pseudocode. Computational parables are then presented, including a parable relating to the slaughter of innocents through dispositional contagion. This part also shows how the model can capture three spatially explicit examples in which affect and probability change on different time scales.

scholarly journals RURAL-URBAN MIGRATION IN D-DIMENSIONAL LATTICES

2005 ◽  
Vol 16 (12) ◽  
pp. 1831-1840 ◽  
Author(s):  
AQUINO L. ESPÍNDOLA ◽  
T. J. P. PENNA ◽  
JAYLSON J. SILVEIRA
Keyword(s):  
Spatial Distribution ◽  
Computational Model ◽  
Higher Dimensions ◽  
Urban Migration ◽  
Agent Based ◽  
Rural Urban Migration ◽  
Migratory Process

The rural-urban migration phenomenon is analyzed by using an agent-based computational model. Agents are placed on lattices which dimensions varying from d =2 up to d =7. The localization of the agents in the lattice defines that their social neighborhood (rural or urban) is not related to their spatial distribution. The effect of the dimension of lattice is studied by analyzing the variation of the main parameters that characterizes the migratory process. The dynamics displays strong effects even for around one million of sites, in higher dimensions (d =6, 7).

Examining the Myth of Money with Agent-Based Modelling

2008 ◽  
pp. 252-263 ◽  
Author(s):  
Satoru Yamadera
Keyword(s):  
Social Sciences ◽  
Computational Model ◽  
Intrinsic Value ◽  
Agent Based Modeling ◽  
Agent Based ◽  
Economic Theories ◽  
Agent Based Modelling ◽  
Simulation Results ◽  
Classical Economic ◽  
Theories Of Money

This chapter presents an agent-based computational model of the emergence of money. It is based on classical economic theories of money, advocating that money is a symbol of credibility. The most interesting and mysterious feature of money is a departure of its face value from its intrinsic value. People accept and appreciate a piece of paper because it is believed as money. The model examines how such belief creates money in a society. Further more, by incorporating spatial activities of agents into the simulations, the model can examine various hypotheses which were difficult to be examined in previous approaches. The simulation results show that parameters such as credibility and communication between agents will affect the outcomes. The model not only provides the foundation for more generalized theory of money, but also demonstrates that agent-based modeling can be an effective tool to examine various hypotheses of social sciences.

FUNCTIONAL MODULARITY IN THE FUNDAMENTALS OF ECONOMIC THEORY: TOWARD AN AGENT-BASED ECONOMIC MODELING OF THE EVOLUTION OF TECHNOLOGY

2004 ◽  
Vol 18 (17n19) ◽  
pp. 2376-2386 ◽  
Author(s):  
SHU-HENG CHEN ◽  
BIN-TZONG CHIE
Keyword(s):  
Economic Theory ◽  
Genetic Programming ◽  
Computational Model ◽  
Economic Model ◽  
Economic Modeling ◽  
Agent Based ◽  
Evolution Of Technology ◽  
Computational Economic

No matter how commonly the term innovation has been used in economics, a concrete analytical or computational model of innovation is not yet available. This paper argues that a breakthrough can be made with genetic programming, and proposes a functional-modularity approach to an agent-based computational economic model of innovation.

scholarly journals TonalEmergence: An Agent-Based Model of Tonal Coordination

2021 ◽  
Author(s):  
Matthew Setzler ◽  
Robert Goldstone
Keyword(s):  
Computational Model ◽  
Empirical Studies ◽  
Human Cognition ◽  
Coordination Mechanisms ◽  
Agent Based Model ◽  
Agent Based ◽  
Music Improvisation ◽  
Interacting Agents ◽  
Mutual Adaptation ◽  
Complex Coordination

Humans have a remarkable capacity for coordination. Our ability to interact and act jointly in groups is crucial to our success as a species. Joint Action (JA) research has often concerned itself with simplistic behaviors in highly constrained laboratory tasks. But there has been a growing interest in understanding complex coordination in more open-ended contexts. In this regard, collective music improvisation has emerged as a fascinating model domain for studying basic JA mechanisms in an unconstrained and highly sophisticated setting. A number of empirical studies have begun to elucidate coordination mechanisms underlying joint musical improvisation, but these empirical findings have yet to be cached out in a working computational model. The present work fills this gap by presenting TonalEmergence, an idealized agent-based model of improvised musical coordination. TonalEmergence models the coordination of notes played by improvisers to generate harmony (i.e., tonality), by simulating agents that stochastically generate notes biased towards maximizing harmonic consonance given their partner's previous notes. The model replicates an interesting empirical result from a previous study of professional jazz pianists: that feedback loops of mutual adaptation between interacting agents support the production of consonant harmony. The model is further explored to show how complex tonal dynamics, such as the production and dissolution of stable tonal centers, are supported by agents that are characterized by 1) a tendency to strive toward consonance, 2) stochasticity, and 3) a limited memory for previously played notes. TonalEmergence thus provides a grounded computational model to simulate and probe the coordination mechanisms underpinning one of the more remarkable feats of human cognition: collective music improvisation.

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