MULTIͳAGENT SYSTEMS ͳ MODELING, INTERACTIONS, SIMULATIONS AND CASE STUDIES Edited by Faisal Alkhateeb, Eslam Al Maghayreh and Iyad Abu Doush Multi-Agent Systems - Modeling, Interactions, Simulations and Case Studies Edited by Faisal Alkhateeb, Eslam Al Maghayreh and Iyad Abu Doush Published by InTech Janeza Trdine 9, 51000 Rijeka, Croatia Copyright © 2011 InTech All chapters are Open Access articles distributed under the Creative Commons Non Commercial Share Alike Attribution 3.0 license, which permits to copy, distribute, transmit, and adapt the work in any medium, so long as the original work is properly cited. After this work has been published by InTech, authors have the right to republish it, in whole or part, in any publication of which they are the author, and to make other personal use of the work. Any republication, referencing or personal use of the work must explicitly identify the original source. Statements and opinions expressed in the chapters are these of the individual contributors and not necessarily those of the editors or publisher. No responsibility is accepted for the accuracy of information contained in the published articles. The publisher assumes no responsibility for any damage or injury to persons or property arising out of the use of any materials, instructions, methods or ideas contained in the book. Publishing Process Manager Katarina Lovrecic Technical Editor Teodora Smiljanic Cover Designer Martina Sirotic Image Copyright Yuri Arcurs, 2010. Used under license from Shutterstock.com First published March, 2011 Printed in India A free online edition of this book is available at www.intechopen.com Additional hard copies can be obtained from orders@intechweb.org Multi-Agent Systems - Modeling, Interactions, Simulations and Case Studies Edited by Faisal Alkhateeb, Eslam Al Maghayreh and Iyad Abu Doush p. cm. ISBN 978-953-307-176-3 free online editions of InTech Books and Journals can be found at www.intechopen.com Part 1 Chapter 1 Chapter 2 Chapter 3 Chapter 4 Chapter 5 Chapter 6 Chapter 7 Chapter 8 Preface IX Multi-Agent Systems Modeling 1 Agent-Based Modeling and Simulation of Species Formation Processes 3 Rafal Drezewski A Multi-Agent based Multimodal System Adaptive to the User’s Interaction Context 29 Manolo Dulva Hina, Chakib Tadj, Amar Ramdane-Cherif and Nicole Levy Scenario-Based Modeling of Multi-Agent Systems 57 Armin Stranjak, Igor Čavrak and Mario Žagar Modelling Multi-Agent System using Different Methodologies 77 Vera Maria B. Werneck, Rosa Maria E. Moreira Costa and Luiz Marcio Cysneiros The Agent Oriented Multi Flow Graphs Specification Model 97 I. D. Zaharakis Multi-Agent Models in Workflow Design 131 Victoria Iordan Evolutionary Reduction of the Complexity of Software Testing by Using Multi-Agent System Modeling Principles 149 Arnicans G. and Arnicane V. An Approach to Operationalize Regulative Norms in Multiagent Systems 175 Carolina Howard Felicíssimo, Jean-Pierre Briot and Carlos José Pereira de Lucena Contents Contents VI Interaction and Decision Making on Agent Environments 201 Agent-Environment Interaction in MAS - Introduction and Survey 203 Joonas Kesäniemi and Vagan Terziyan A Dependable Multi-Agent System with Self-Diagnosable Function 227 Keinosuke Matsumoto, Akifumi Tanimoto and Naoki Mori Evolution of Adaptive Behavior toward Environmental Change in Multi-Agent Systems 241 Atsuko Mutoh, Hideki Hashizume, Shohei Kato and Hidenori Itoh Evolutionary Adaptive Behavior in Noisy Multi-Agent System 255 Takamasa Iio, Ivan Tanev, Katsunori Shimohara and Mitsunori Miki Data Mining for Decision Making in Multi-Agent Systems 273 Hani K. Mahdi, Hoda K. Mohamed and Sally S. Attia Multi-Agent Systems Simulation 299 Decision Support based on Multi-Agent Simulation Algorithms with Resource Conversion Processes Apparatus Application 301 Konstantin Aksyonov, Eugene Bykov, Leonid Dorosinskiy, Elena Smoliy and Olga Aksyonova Agent-based Simulation Analysis for Effectiveness of Financing Public Goods with Lotteries 327 Ichiro Nishizaki, Tomohiko Sasaki and Tomohiro Hayashida Case Studies 357 Integrating RFID in MAS through “Sleeping” Agents: a Case Study 359 Vincenzo Di Lecce , Alberto Amato and Marco Calabrese A Multi-Agent Approach to Electric Power Systems 369 Nikolai I. Voropai, Irina N. Kolosok, Lyudmila V. Massel, Denis A. Fartyshev, Alexei S. Paltsev and Daniil A. Panasetsky Multi-Agent Systems and Blood Cell Formation 395 Bessonov Nikolai, Demin Ivan, Kurbatova Polina, Pujo-Menjouet Laurent and Volpert Vitaly Part 2 Chapter 9 Chapter 10 Chapter 11 Chapter 12 Chapter 13 Part 3 Chapter 14 Chapter 15 Part 4 Chapter 16 Chapter 17 Chapter 18 Contents VII Identification of Relevant Genes with a Multi-Agent System using Gene Expression Data 425 Edna Márquez, Jesús Savage, Christian Lemaitre, Jaime Berumen, Ana Espinosa and Ron Leder Collecting and Classifying Large Scale Data to Build an Adaptive and Collective Memory: a Case Study in e-Health for a Pro-active Management 439 Singer Nicolas, Trouilhet Sylvie, Rammal Ali and Pécatte Jean-Marie Developing a Multi-agent Software to Support the Creation of Dynamic Virtual Organizations aimed at Preventing Child Abuse Cases 455 Pedro Sanz Angulo and Juan José de Benito Martín Obtaining Knowledge of Genes’ Behavior in Genetic Regulatory System by Utilizing Multiagent Collaborative Computation 475 Adang Suwandi Ahmad and Arwin Datumaya Wahyudi Sumari Chapter 19 Chapter 20 Chapter 21 Chapter 22 Pref ac e A multi-agent system (MAS) is a system composed of multiple interacting intelligent agents. Multi-agent systems can be used to solve problems which are diffi cult or im- possible for an individual agent or monolithic system to solve. Agent systems are open and extensible systems that allow for the deployment of autonomous and proactive so ware components. Multi-agent systems have been brought up and used in several application domains. This book is a collection of 22 excellent works on multi-agent systems divided into four sections: Multi-Agent Systems Modeling, Interaction and Decision Making on Agent Environments, Multi-Agent Systems Simulation and Case Studies. Faisal Alkhateeb, Eslam Al Maghayreh and Iyad Abu Doush, Yarmouk University, Jordan [...]... local minima in the multi- modal fitness landscape—see section 4) Flock splits into two flocks when there exists an agent within the flock which in fact occupies different ecological niche than other agents in the flock and there is 12 Multi- Agent Systems - Modeling, Interactions, Simulations and Case Studies Fig 2 Multi- Agent System with Flock Formation Mechanisms no existing flock that such agent can migrate... that can reproduce and that is located within the same vertice of the environment Reproduction takes place with the use of recombination and mutation operators—operators from evolution strategies were used: intermediate 10 Multi- Agent Systems - Modeling, Interactions, Simulations and Case Studies Fig 1 Multi- Agent System with Geographical Barriers recombination Booker et al (1997), and mutation with... has already been applied in several computational systems The BSMAS approach allows for agent- based modeling of biological and social phenomena due to the possibility of defining in a very natural way of all 26 4000 1400 Multi- Agent Systems - Modeling, Interactions, Simulations and Case Studies 0 0 200 1000 2000 Number of agents 1000 800 600 400 Number of agents aBSMAS fBSMAS sBSMAS 3000 1200 aBSMAS fBSMAS... maintained—agents are spread over rather large areas of fitness landscape Fig 12– 15 show speciation processes taking place under second model multi- agent system with flocks As it can be seen in the figures, the speciation takes place and the diversity within the species is rather low, as compared to aBSMAS model, and especially sBSMAS model Also, 20 Multi- Agent Systems - Modeling, Interactions, Simulations and. ..Part 1 Multi- Agent Systems Modeling 1 Agent- Based Modeling and Simulation of Species Formation Processes Rafal Drezewski Department of Computer Science, AGH University of Science and Technology Poland 1 Introduction Agent- based modeling and simulation becomes increasingly popular in social and biological sciences It is due to the fact that agent- based models allow to elegant and explicitly... vertice 16 Multi- Agent Systems - Modeling, Interactions, Simulations and Case Studies male agent type is defined in the following way: male = Gl male = gl1 , gl2 , gl3 , Attr male = genotype , Actmale = die, reproduce, get_resource, migrate, , ResT male = ResT, In f T male = ∅, ObjT male = ∅, AgT (41) male =∅ where gl1 is the goal “get resource from environment”, gl2 is the goal “reproduce”, and gl3 is... assumed (see fig 5) Schwefel fitness landscape is defined as follows (Potter (1997)): f3 (x ) = n ∑ i =1 − xi ∗ sin | xi | xi ∈ [−500.0; 500.0] for i = 1, , n (49) 18 Multi- Agent Systems - Modeling, Interactions, Simulations and Case Studies Rastrigin 50 40 30 20 10 2 1 60 50 40 30 20 10 0 0 2 -1 1 -2 0 -2 -2 -1 -1 0 1 2 -1 0 1 -2 2 (a) (b) Fig 5 Rastrigin fitness landscape Schwefel 400 800 600 400 200... computational model, and the possibility of introducing new evolutionary operators and social relations, which were hard or impossible to introduce in the case of “classical” evolutionary computations Co-evolutionary multi- agent systems (CoEMAS) utilizing mentioned above second kind of approach to merging evolutionary computations and multi- agent systems have already been ˙ applied with good results to multi- modal... formation processes in fBSMAS with Michalewicz fitness landscape 3 22 Multi- Agent Systems - Modeling, Interactions, Simulations and Case Studies 2 1 1 -1 -2 0 0 -1 -1 1 0 -2 2 -2 2 -2 -1 (a) t=0 0 1 2 (b) t=50 2 2 1 1 0 0 -1 -1 -2 -2 -1 0 1 2 -2 -2 -1 (c) t=500 0 1 2 (d) t=5000 Fig 13 Species formation processes in fBSMAS with Rastrigin fitness landscape 400 400 200 200 0 0 -200 -200 -400 -400 -200 0... formation processes in sBSMAS with Michalewicz fitness landscape 3 24 Multi- Agent Systems - Modeling, Interactions, Simulations and Case Studies 2 1 1 -1 -2 0 0 -1 -1 1 0 -2 2 -2 2 -2 -1 (a) t=0 0 1 2 (b) t=50 2 2 1 1 0 0 -1 -1 -2 -2 -1 0 1 2 -2 -2 -1 (c) t=500 0 1 2 (d) t=5000 Fig 17 Species formation processes in sBSMAS with Rastrigin fitness landscape 400 400 200 200 0 0 -200 -200 -400 -400 -200 0 . MULTI AGENT SYSTEMS ͳ MODELING, INTERACTIONS, SIMULATIONS AND CASE STUDIES Edited by Faisal Alkhateeb, Eslam Al Maghayreh and Iyad Abu Doush Multi- Agent Systems - Modeling, Interactions, Simulations. sections: Multi- Agent Systems Modeling, Interaction and Decision Making on Agent Environments, Multi- Agent Systems Simulation and Case Studies. Faisal Alkhateeb, Eslam Al Maghayreh and Iyad. attributes of agent ag—it can change during its lifetime; 8 Multi- Agent Systems - Modeling, Interactions, Simulations and Case Studies • Act ag ⊆ Act is the set of actions, which agent ag can