scholarly journals An Empirical Validation Protocol for Large-Scale Agent-Based Models

2017 ◽  
Author(s):  
Sylvain Barde ◽  
Sander van der Hoog
Keyword(s):  
Large Scale ◽  
Empirical Validation ◽  
Agent Based Models ◽  
Agent Based

Improving the Efficiency of Large-Scale Agent-Based Models Using Compression Techniques

2012 ◽  
pp. 301-326
Author(s):  
Mitchell Welch ◽  
Paul Kwan ◽  
A.S.M. Sajeev ◽  
Graeme Garner
Keyword(s):  
Large Scale ◽  
Agent Based Models ◽  
Agent Based ◽  
Agent Based Modelling ◽  
Livestock Disease ◽  
Interacting Agents ◽  
National Model ◽  
Complex Phenomena ◽  
Modelling System

Agent-based modelling is becoming a widely used approach for simulating complex phenomena. By making use of emergent behaviour, agent based models can simulate systems right down to the most minute interactions that affect a system’s behaviour. In order to capture the level of detail desired by users, many agent based models now contain hundreds of thousands and even millions of interacting agents. The scale of these models makes them computationally expensive to operate in terms of memory and CPU time, limiting their practicality and use. This chapter details the techniques for applying Dynamic Hierarchical Agent Compression to agent based modelling systems, with the aim of reducing the amount of memory and number of CPU cycles required to manage a set of agents within a model. The scheme outlined extracts the state data stored within a model’s agents and takes advantage of redundancy in this data to reduce the memory required to represent this information. The techniques show how a hierarchical data structure can be used to achieve compression of this data and the techniques for implementing this type of structure within an existing modelling system. The chapter includes a case study that outlines the practical considerations related to the application of this scheme to Australia’s National Model for Emerging Livestock Disease Threats that is currently being developed.

scholarly journals Empirical Validation in Agent-based Models: Introduction to the Special Issue

2007 ◽  
Vol 30 (3) ◽  
pp. 189-194 ◽  
Author(s):  
G. Fagiolo ◽  
C. Birchenhall ◽  
P. Windrum
Keyword(s):  
Empirical Validation ◽  
Special Issue ◽  
Agent Based Models ◽  
Agent Based

COMPUTATIONAL FEATURES OF AGENT-BASED MODELS

2005 ◽  
Vol 02 (01) ◽  
pp. 33-48 ◽  
Author(s):  
MASSIMO BERNASCHI ◽  
FILIPPO CASTIGLIONE
Keyword(s):  
Data Structures ◽  
Large Scale ◽  
Agent Based Modeling ◽  
System Response ◽  
Agent Based Models ◽  
Design Data ◽  
Agent Based ◽  
Data Structures And Algorithms ◽  
Immune System Response ◽  
Large Scale Simulations

Agent-based modeling allows the description of very complex systems. To run large scale simulations of agent-based models in a reasonable time, it is crucial to carefully design data structures and algorithms. We describe the main computational features of agent-based models and report about the solutions we adopted in two applications: The simulation of the immune system response and the simulation of the stock market dynamics.

Empirical Validation of Agent-Based Models

2018 ◽  
pp. 163-182 ◽  
Author(s):  
Giorgio Fagiolo ◽  
Matteo Richiardi
Keyword(s):  
Empirical Validation ◽  
Agent Based Models ◽  
Agent Based

scholarly journals Intra-group decision-making in agent-based models

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Allegra A. Beal Cohen ◽  
Rachata Muneepeerakul ◽  
Gregory Kiker
Keyword(s):  
Decision Making ◽  
Functional Groups ◽  
Group Dynamics ◽  
Group Decision Making ◽  
Local Governments ◽  
Large Scale ◽  
Group Decision ◽  
Social Systems ◽  
Agent Based Models ◽  
Agent Based

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.

Recordkeeping and Human Evolution

2006 ◽  
Vol 20 (3) ◽  
pp. 201-229 ◽  
Author(s):  
Sudipta Basu ◽  
Gregory B. Waymire
Keyword(s):  
Human Brain ◽  
Division Of Labor ◽  
Human Evolution ◽  
Evolutionary Theory ◽  
Large Scale ◽  
Agent Based Models ◽  
Agent Based ◽  
Weights And Measures ◽  
Language And Law ◽  
Evolutionary Role

We seek to characterize the evolutionary role played by the transactional record that is the foundation of modern accounting. We theorize that systematic recordkeeping crystallizes memory and, along with other institutions (e.g., law, weights, and measures), promotes the trust necessary for large-scale human cooperation. Our theory yields two predictions: (1) permanent records emerge to supplement memory when complex intertemporal exchange between strangers becomes more common and (2) systematic records and other exchange-supporting institutions co-evolve and feed back to increase gains from economic coordination and division of labor. Many aspects of ancient Mesopotamian recordkeeping are consistent with these hypotheses, suggesting that our evolutionary theory is plausible. We outline ways to directly test our predictions with experiments, ethnographies, and agent-based models, and describe other techniques that can be used to explore the co-evolution of accounting with the human brain, language, and law.

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