X-Machines for Agent-Based Modeling (Open Access): FLAME Perspectives, 1st Edition (Hardback) book cover

X-Machines for Agent-Based Modeling (Open Access)

FLAME Perspectives, 1st Edition

By Mariam Kiran

Chapman and Hall/CRC

320 pages | 50 B/W Illus.

Book Content Available Open Access*
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*Open Access content has been made available under a Creative Commons Attribution-Non Commercial-No Derivatives (CC-BY-NC-ND) license

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Hardback: 9781498723855
pub: 2017-08-15
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Description

From the Foreword:

"This book exemplifies one of the most successful approaches to modeling and simulating [the] new generation of complex systems. FLAME was designed to make the building of large scale complex systems models straightforward and the simulation code that it generates is highly efficient and can be run on any modern technology. FLAME was the first such platform that ran efficiently on high performance parallel computers and a version for GPU technology is also available. At its heart, and the reason why it is so efficient and robust, is the use of a powerful computational model ‘Communicating X-machines’ which is general enough to cope with most types of modelling problems. As well as being increasingly important in academic research, FLAME is now being applied in industry in many different application areas. This book describes the basics of FLAME and is illustrated with numerous examples."

—Professor Mike Holcombe, University of Sheffield, UK

Agent-based models have shown applications in various fields such as biology, economics, and social science. Over the years, multiple agent-based modeling frameworks have been produced, allowing experts with non-computing background to easily write and simulate their models. However, most of these models are limited by the capability of the framework, the time it takes for a simulation to finish, or how to handle the massive amounts of data produced. FLAME (Flexible Large-scale Agent-based Modeling Environment) was produced and developed through the years to address these issues.

This book contains a comprehensive summary of the field, covers the basics of FLAME, and shows how concepts of X-machines, can be stretched across multiple fields to produce agent models. It has been written with several audiences in mind. First, it is organized as a collection of models, with detailed descriptions of how models can be designed, especially for beginners. A number of theoretical aspects of software engineering and how they relate to agent-based models are discussed for students interested in software engineering and parallel computing. Finally, it is intended as a guide to developers from biology, economics, and social science, who want to explore how to write agent-based models for their research area. By working through the model examples provided, anyone should be able to design and build agent-based models and deploy them. With FLAME, they can easily increase the agent number and run models on parallel computers, in order to save on simulation complexity and waiting time for results.

Because the field is so large and active, the book does not aim to cover all aspects of agent-based modeling and its research challenges. The models are presented to show researchers how they can build complex agent functions for their models. The book demonstrates the advantage of using agent-based models in simulation experiments, providing a case to move away from differential equations and build more reliable, close to real, models.

The Open Access version of this book, available at https://doi.org/10.1201/9781315370729, has been made available under a Creative Commons Attribution-Non Commercial-No Derivatives 4.0 license.

Table of Contents

Setting the Stage: Complex Systems, Emergence and Evolution

Complex and Adaptive systems

What is Chaos?

Constructing Artificial Systems

Importance of Emergence

Dynamic Systems

Is there Evolution at Work?

Distributing Intelligence?

Modeling and Simulation

Artificial Agents

Intelligent Agents

Engineering Self-Organising Systems

Agent-Based Modeling Frameworks

Adaptive Agent Design

Mathematical Foundations

Objects or Agents?

Influence of other Research Areas on ABM

Designing X-Agents using FLAME

FLAME and its X-machine methodology

Using Agile Methods to Design Agents

Overview: FLAME version 1.0

Libmboard (FLAME message board library)

FLAME’s Missing Functionality

Getting started with FLAME

Setting up FLAME

Messaging Library: Libmboard

How to run a model?

Implementation Details

Using Grids

Integrating with more Libraries

Writing a Model - Fox and Rabbit Predator Model

8 Enhancing the Environment

Agents in Social Science

Sugarscape Model

Modeling Social Networks

Modeling Pedestrians in Crowds

Agents in Economic Markets and Games

Perfect Rationality vs Bounded Rationality

Learning Firms in a Cournot model

A Virtual Mall Model: Labor and Goods Market Combined

Programming Games

Learning in an Iterated Prisonner’s Dilemma Game

Multi-Agent Systems and Games

Agents in Biology

Example Models

Modeling Epithelial Tissue

Modeling the Drosophila Embryo Development

Output a Particular File for Analysis

Modeling Pharaoh’s Ants (Monomorium pharaonis

Modeling Drugs Delivery for Cancer Treatment

Testing Agent Behavior

Unit and System Testing

Statistical Testing of Data

Statistics Testing on Code

Testing Simulation Durations

FLAME’s Future

FLAME to FLAME GPU

Commercial applications of FLAME

About the Author

Dr. Mariam Kiran is a well-recognized researcher in agent-based modeling, high performance simulations and cloud computing. She has published numerous papers in these fields, both, in theory and practical implementations, exploiting grid and cloud ecosystems for improving computational performance for multi-domain research. She has an extensive record of research collaborations across the world, serving as a board member for Complex Systems research in CoMSES, and several joint projects funded by European Research and UK Engineering Council. She is also active in education research of software engineering in team building and writing software for simulations.

Mariam Kiran received her PhD in Computer Science from University of Sheffield, Sheffield UK in 2010. She is currently involved in many projects at Lawrence Berkeley National Labs, California, optimizing high performance computing problems across various disciplines. Prior to this, she was working as an Associate Professor at University of Bradford, leading the Cloud Computing research in the School.

About the Series

Chapman & Hall/CRC Computer and Information Science Series

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Subject Categories

BISAC Subject Codes/Headings:
COM000000
COMPUTERS / General
COM037000
COMPUTERS / Machine Theory
SCI008000
SCIENCE / Life Sciences / Biology / General
TEC008000
TECHNOLOGY & ENGINEERING / Electronics / General