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Agent-based Modeling

Adam Getchell Department of Physics University of California, Davis acgetchell@ucdavis.edu

June 9, 2008

Abstract

The theory and practice of agent-based modeling is reviewed, and agent-based modeling toolkits are evaluated and discussed. A tractable selection of toolkits, RepastPy, Repast Simphony, and breve are then employed to develop and visualize a series of increasingly sophisticated agent-based models, starting with a simple network-interaction diagram and proceeding onto the Boids 3D flock simulation, a 3D collision and gravity system, the chaotic Gray Scott diffusion reaction, a sophisticated agent behaviors game of Capture the Flag, finally culminating with an complex Boids evolutionary swarm simulation. To accomplish the latter, genetic programming techniques are briefly reviewed. Finally, an overview is presented with future directions.

INTRODUCTION

The use of computer systems to solve problems of interest in physics, biology, chemistry, economics, and social sciences has been well-established for decades. The great advances in computing power, software development, computer graphics, communications networks, and a host of other technologies have elevated the domain of applicability to problem solving from simple arithmetic calculations to advanced numerical methods and the creation of large simulations solving myriad systems of complex equations in real-time.

A recent development has been the introduction of the Agent-Based Modeling paradigm, which has proven useful for a wide range of problems in physics and chaotic attractors [1], biology [2], economics [3], social science [4], and geospatial simulations [5]. Commensurate with this new paradigm has been the development of a range of toolkits to apply Agent-Based modeling to a particular range of problems.

This purpose of this paper is to provide a general introduction to Agent-Based modeling and demonstrate its use in the modeling of a chaotic system. Organization is as follows: Section I begins with a general discussion of Agent-Based Modeling (hereafter ABM), including definitions and characteristics of systems amenable to this approach. Section II will provide an up-to-date review of the various Swarm modeling toolkits currently available at this time of writing. Section III will show the use of a particular toolkit, Repast, using both the simplified RepastPy interface and the more complex RepastS integrated development environment (IDE), and cover the development of a simple swarm model. Section IV will cover the simulation of the chaotic system ______, and Section V will wrap-up with conclusions and further references.

SECTION I - OVERVIEW

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