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E-grāmata: Advances in Practical Multi-Agent Systems

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  • Formāts: PDF+DRM
  • Sērija : Studies in Computational Intelligence 325
  • Izdošanas datums: 12-Oct-2010
  • Izdevniecība: Springer-Verlag Berlin and Heidelberg GmbH & Co. K
  • Valoda: eng
  • ISBN-13: 9783642160981
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Advances in Practical Multi-Agent SystemsPalielināt
  • Formāts: PDF+DRM
  • Sērija : Studies in Computational Intelligence 325
  • Izdošanas datums: 12-Oct-2010
  • Izdevniecība: Springer-Verlag Berlin and Heidelberg GmbH & Co. K
  • Valoda: eng
  • ISBN-13: 9783642160981
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Multi-Agent System (MAS) is an exciting, emerging paradigm expected to play a key role in many society-changing practices. The International Conference on Principles and Practice of Multi-Agent Systems (PRIMA) is a leading scientific conference for research on intelligent agent systems and multi-agent systems, attracting high quality, state-of-the-art research from all over the world. PRIMA’09 was the 12th in the series of PRIMA conferences and was held in Nagoya, Japan. Beside a single-track main conference, PRIMA’09 also included a number of workshops which were designed to provide a forum for researchers and practitioners to present and exchange the latest developments at the MAS frontier. This book constitutes the post-proceedings of workshops under PRIMA’09. Readers will be able to explore a diverse range of topics and detailed discussions related to a number of important themes in our ever changing world. This collection plays an important role in bridging the gap between MAS theory and practice. It emphasizes the importance of MAS in the research and development of smart power grid systems, decision support systems, optimization and analysis systems for road traffic and markets, environmental monitoring and simulation, and in many other real-world applications and publicizes and extends MAS technology to many domains in this fast moving information age.

This state-of-the-art book covers the use of technology to assist collaboration among humans and software mechanisms, agent-based simulation in finance, economics and social science; environmental monitoring and disaster management.
Part I Agent-Based Collaboration, Coordination and Decision Support
DGF: Decentralized Group Formation for Task Allocation in Complex Adaptive Systems
3(18)
Dayong Ye
Minjie Zhang
Danny Sutanto
1 Introduction
3(2)
2 Decentralized Group Formation Algorithm
5(5)
2.1 Problem Description
5(2)
2.2 The Principle of Decentralized Group Formation (DGF) Algorithm
7(3)
3 System Adaptation Strategy
10(1)
4 Experiment and Analysis
11(7)
4.1 Greedy Distributed Allocation Protocol
11(1)
4.2 Experiment Setting
12(2)
4.3 Experiment Results
14(4)
4.4 Experiment Analysis
18(1)
5 Conclusion and Future Work
18(1)
References
18(3)
Cellular Automata and Immunity Amplified Stochastic Diffusion Search
21(12)
Duncan Coulter
Elizabeth Ehlers
1 Background
21(4)
1.1 Stochastic Diffusion Search
22(2)
1.2 Cellular Automata
24(1)
1.3 Clonal Selection
25(1)
2 The CAIA-SDS Model
25(5)
2.1 Model Development
26(2)
2.2 Model Implementation
28(2)
3 Results
30(1)
4 Conclusion
31(1)
References
31(2)
Related Word Extraction Algorithm for Query Expansion---An Evaluation
33(16)
Tetsuya Oishi
Tsunenori Mine
Ryuzo Hasegawa
Hiroshi Fujita
Miyuki Koshimura
1 Introduction
33(1)
2 Related Work
34(1)
3 Experimental Condition
35(2)
3.1 Query Expansion System
36(1)
3.2 Types of Queries
36(1)
4 Score of Similarity between Related Words and User's Intent
37(3)
4.1 RWEA
37(2)
4.2 RSV
39(1)
4.3 The Method Combining RWEA and RSV
40(1)
5 Experiment
40(7)
5.1 Experimental Methods
40(3)
5.2 Result
43(4)
6 Conclusion
47(1)
References
47(2)
Verification of the Effect of Introducing an Agent in a Prediction Market
49(14)
Takuya Yamamoto
Takayuki Ito
1 Introduction
49(2)
2 Research Background
51(7)
2.1 Prediction Market
51(1)
2.2 Structure of a Predicted Value
51(2)
2.3 Comparison of the Prediction Method
53(2)
2.4 Collective Intelligence
55(1)
2.5 Examples of Prediction Markets
56(1)
2.6 Related Work
57(1)
3 Current Research and Problems
58(1)
4 Experiment Outline and Discussion
59(2)
4.1 Zocalo
59(1)
4.2 Experiment
60(1)
4.3 Results and Discussion
60(1)
5 Conclusion
61(1)
References
61(2)
A Cognitive Map Network Model
63(10)
Yuan Miao
1 Introduction
63(2)
2 A Cognitive Map Network Model
65(4)
2.1 A Market Cognitive Ecosystem
65(1)
2.2 Consumer Active Cognitive Agents
66(1)
2.3 Market Responsive Cognitive Agent
67(1)
2.4 Market Responsive Cognitive Agent
68(1)
3 Analysis of the Economic System with the CM Network Model
69(2)
4 Conclusions
71(1)
References
71(2)
Coordination Strategies and Techniques in Distributed Intelligent Systems---Applications
73(22)
Abdeslem Boukhtouta
Jean Berger
Ranjeev Mittu
Abdellah Bedrouni
1 Introduction
74(1)
2 Defence
75(5)
2.1 Control of Swarms of Unmanned Aerial Vehicles (UAVs)
75(1)
2.2 Coordination for Joint Fires Support (JFS)
76(1)
2.3 Simulation of C4I Interoperability
76(2)
2.4 Coalition Interoperability
78(1)
2.5 Tiered Systems
79(1)
3 Transportation
80(1)
3.1 Air Traffic Flow Management
80(1)
3.2 Other Transportation and Network Management Applications
81(1)
4 Healthcare---Monitoring Glucose Levels
81(2)
5 Communications Networks
83(3)
5.1 Fault Diagnosis
83(2)
5.2 Routing in Telecommunications
85(1)
6 E-Business
86(1)
6.1 Supply Chain Management
86(1)
6.2 Manufacturing Systems
87(1)
7 Emergency Management and Disaster Relief
87(4)
8 Ambient Intelligence
91(1)
9 Conclusion
91(1)
References
92(3)
Multi-Agent Area Coverage Using a Single Query Roadmap: A Swarm Intelligence Approach
95(18)
Ali Nasri Nazif
Alireza Davoodi
Philippe Pasquier
1 Introduction
95(2)
2 Preliminaries and Related Works
97(2)
2.1 Roadmaps
97(1)
2.2 Multi-Agent Environment Coverage
98(1)
3 Weighted Multi-Agent RRT
99(3)
4 Agent Architecture
102(4)
5 Exploration of WMA-RRT Roadmap
106(1)
6 Implementation and Experimental Results
107(3)
6.1 Implementation
107(1)
6.2 Experimental Results
108(2)
7 Future Works and Conclusion
110(1)
References
111(2)
An Approach for Learnable Context-Awareness System by Reflecting User Feedback
113(16)
In Woo Jang
Chong-Woo Woo
1 Introduction
113(1)
2 Related Studies
114(1)
2.1 Context-Awareness System
114(1)
2.2 Agent in Previous Context-Awareness System
115(1)
3 System Architecture
115(9)
3.1 Context Management Agent (CMA)
116(3)
3.2 Situation Reasoning Agent (SRA)
119(5)
4 Simulated Experimentation
124(2)
5 Conclusion
126(1)
References
127(2)
A Hybrid Multi-Agent Framework for Load Management in Power Grid Systems
129(20)
Minjie Zhang
Dayong Ye
Quan Bai
Danny Sutanto
Kashem Muttaqi
1 Introduction
129(1)
2 Related Work
130(2)
3 Framework Architecture and Detailed Design
132(7)
3.1 Centralized Architecture vs. Decentralized Architecture
132(1)
3.2 Design Consideration
133(1)
3.3 Hybrid Architecture
134(5)
3.4 Agents in HMAF
139(1)
4 Operation of HMAF
139(2)
5 Conclusion
141(1)
References
142(7)
Part II Agent-Based Simulation for Complex Systems: Application to Economics, Finance and Social Sciences
Financial Frictions and Money-Driven Variability in Velocity
149(18)
Jose J. Cao-Alvira
1 Introduction
149(2)
2 Cash-in-Advance Model Economy
151(5)
2.1 Discussion of the Economy
151(3)
2.2 Analytical Steady States
154(1)
2.3 Equilibrium of the Economy
154(1)
2.4 State Space and Functional Forms of the Economy
154(2)
3 Solution Methodology
156(3)
3.1 Algorithm Chronology
158(1)
4 Business Cycle Properties
159(6)
4.1 Calibration
159(1)
4.2 Model Economy Steady States
160(1)
4.3 Velocity at Serially Correlated Money Growth Rates
161(4)
5 Conclusion
165(1)
References
165(2)
Automated Fuzzy Bidding Strategy Using Agent's Attitude and Market Competition
167(14)
Madhu Goyal
Saroj Kaushik
Preetinder Kaur
1 Introduction
167(1)
2 Fuzzy Competition and Attitude Based Bidding Strategy (FCA-Bid)
168(6)
2.1 Attribute Evaluation
170(1)
2.2 Attitude Estimation
171(1)
2.3 Competition Assessment
172(2)
2.4 Agent Price Determination
174(1)
3 Experimental Evaluations
174(5)
4 Conclusions
179(1)
References
179(2)
Resource Allocation Analysis in Perfectly Competitive Virtual Market with Demand Constraints of Consumers
181(20)
Tetsuya Matsuda
Toshiya Kaihara
Nobutada Fuji
1 Introduction
181(1)
2 Virtual Market Structure
182(1)
3 Agent Formulations
183(4)
3.1 Consumer Agents
183(2)
3.2 Producer Agents
185(1)
3.3 Pricing Mechanism
186(1)
4 Computer Simulation and Experimental Results
187(12)
4.1 Exchange Market Analysis
188(4)
4.2 Economic Market Analysis
192(7)
5 Conclusions
199(1)
References
199(2)
Market Participant Estimation by Using Artificial Market
201(16)
Fujio Toriumi
Kiyoshi Izumi
Hiroki Matsui
1 Introduction
201(1)
2 Artificial Market
202(2)
2.1 Artificial Market Framework
202(1)
2.2 Market Mechanism Module
202(1)
2.3 FIX Protocol
203(1)
2.4 Agents
204(1)
2.5 Agent Interface
204(1)
3 Market-Participant Estimation Using Inverse Simulation
204(2)
3.1 Inverse Simulation
204(1)
3.2 Artificial Market Parameters
205(1)
3.3 Evaluation Function
206(1)
4 Trader Agents
206(3)
4.1 Fundamentalist Agents
207(1)
4.2 Chartist Agents
207(1)
4.3 Agent Parameters
207(2)
5 Simulation for Estimating Market Participants
209(4)
5.1 Simulation Settings
209(1)
5.2 Results of Simulation
209(1)
5.3 Analysis of Market Participants
210(3)
6 Conclusion
213(1)
References
213(4)
A Study on the Market Impact of Short-Selling Regulation Using Artificial Markets
217(16)
Isao Yagi
Takanobu Mizuta
Kiyoshi Izumi
1 Introduction
218(1)
2 Construction of Artificial Markets
219(3)
2.1 Agent Models
219(2)
2.2 Modeling of an Agent Influenced by the Trading Rules of High-Performance Agents
221(1)
2.3 Equilibrium Price
222(1)
3 Discussion
222(8)
3.1 Price Variation in the Markets
222(4)
3.2 Agent Transactions
226(3)
3.3 The Market Model in Which the Market Price Affects the Theoretical Price
229(1)
4 Conclusion
230(1)
References
231(2)
Learning a Pension Investment in Consideration of Liability through Business Game
233(18)
Yasuo Yamashita
Hiroshi Takahashi
Takao Terano
1 Introduction
233(2)
2 Method
235(4)
2.1 System of Business Game
235(1)
2.2 Business Game Model
235(4)
3 Result
239(9)
3.1 Case Where Player Has Not Received Professional Training (Student)
240(4)
3.2 Case Where Player Has Received Professional Training (Institutional Investor Affiliation Member)
244(4)
3.3 Consideration
248(1)
4 Conclusion
248(1)
References
249(2)
An Agent-Based Implementation of the Todaro Model
251(16)
Nadjia El Saadi
Alassane Bah
Yacine Belarbi
1 Introduction
251(2)
2 The Todaro Model
253(2)
3 The Migration Agent-Based Model
255(4)
3.1 The Simulator Model
255(1)
3.2 Internal Structure
256(1)
3.3 Interface
257(2)
4 The Simulations
259(5)
4.1 The Scenarios Tested
259(1)
4.2 Simulations Results
260(2)
4.3 Discussion
262(2)
5 Conclusion
264(1)
References
265(2)
New Types of Metrics for Urban Road Networks Explored with S3: An Agent-Based Simulation Platform
267(20)
Cyrille Genre-Grandpierre
Arnaud Banos
1 Why Trying to Change the Current Road Networks "Metric"?
267(3)
1.1 The Farther You Go the More Efficient Is the Road Network
267(1)
1.2 The Indirect Effects of the Current Metric
268(1)
1.3 Traffic Lights for a "Slow Metric"
269(1)
2 Smart Slow Speed (S3): An Agent-Based Simulation Platform
270(5)
2.1 Traffic Lights: Choosing Location and Time Duration
270(3)
2.2 A Microscopic Traffic Model
273(2)
3 First Results
275(8)
3.1 The Metric of the Road Network Depends on
275(4)
3.2 Exploration of the Traffic Model
279(4)
4 Conclusion
283(1)
References
284(3)
Impact of Tenacity upon the Behaviors of Social Actors
287(24)
Joseph El-Gemayel
Christophe Sibertin-Blanc
Paul Chapron
1 Introduction
287(1)
2 The Sociology of Organized Action
288(1)
3 The Meta-Model of Organizations
289(2)
4 Illustrations
291(3)
4.1 The Prisonner Dilemma
291(1)
4.2 The Bolet Case
292(2)
5 Simulation
294(4)
5.1 A Bounded Rationality Algorithm for Actors' Cooperation
294(2)
5.2 The Main Parameters of the Algorithm
296(2)
6 Sensitivity Analysis
298(4)
6.1 Prisoner's Dilemma
299(1)
6.2 The Bolet Case
300(2)
7 Interpretation
302(2)
8 Conclusion
304(1)
References
305(6)
Part III Agent Technology for Environmental Monitoring and Disaster Management
Dynamic Role Assignment for Large-Scale Multi-Agent Robotic Systems
311(16)
Van Tuan Le
Serge Stinckwich
Bouraqadi Noury
Arnaud Doniec
1 Introduction
311(2)
2 Organizational Approach for Multi-robot Systems Overview
313(2)
2.1 The AGR Model
313(1)
2.2 Adapting AGR
314(1)
3 Dynamic Role Assignment
315(4)
3.1 Concepts
315(1)
3.2 Role Assignment Protocol
316(2)
3.3 Example of Role Assignment
318(1)
4 Validation
319(3)
4.1 Validation Scenarios Design and Setup
319(2)
4.2 Push vs. Pull and Optimizations
321(1)
4.3 Impacts of Robots' Density
321(1)
5 Discussion and Open Issues
322(2)
5.1 Toward a Generic Solution
322(1)
5.2 System Re-organization
323(1)
6 Related Work
324(1)
7 Conclusion
325(1)
References
325(2)
Multi-agent System for Blackout Prevention by Means of Computer Simulations
327(12)
Miroslav Prymek
Ales Horak
Adam Rambousek
1 Introduction
327(1)
2 The Rice Power Distribution Network Simulator
328(2)
2.1 Event-Driven Agents
329(1)
3 Model Situation Implementation
330(6)
3.1 The Network Topology
331(1)
3.2 The Source Node
331(2)
3.3 The Power Line
333(1)
3.4 The Consumer Node
334(2)
4 Conclusions
336(1)
References
336(3)
Asking for Help Through Adaptable Autonomy in Robotic Search and Rescue
339(20)
Breelyn Kane
Prasanna Velagapudi
Paul Scerri
1 Introduction
339(2)
2 Problem
341(2)
3 Concept
343(2)
4 Algorithm
345(4)
4.1 Self-monitoring
345(2)
4.2 Decision Model
347(2)
5 Results
349(6)
5.1 USARSim
349(3)
5.2 SimpleSim
352(3)
6 Related Work
355(1)
7 Conclusion and Future Work
355(1)
References
356(3)
Conceptual Framework for Design of Service Negotiation in Disaster Management Applications
359(18)
Costin Badica
Mihnea Scafes
1 Introduction
359(3)
2 Service Negotiation
362(1)
3 Conceptual Framework
363(9)
3.1 Negotiation Steps
364(1)
3.2 Negotiation Subject
364(2)
3.3 Agent Preferences
366(3)
3.4 Levels in Negotiation Specification
369(1)
3.5 Example
370(2)
4 Related Work
372(1)
5 Conclusions and Future Work
373(1)
References
374(3)
An Optimized Solution for Multi-Agent Coordination Using Integrated GA-Fuzzy Approach in Rescue Simulation Environment
377(12)
Mohammad Goodarzi
Ashkan Radmand
Eslam Nazemi
1 Introduction
377(1)
2 Environment Categorizing
378(2)
2.1 Data Categorizing
378(2)
2.2 Parameters Definition
380(1)
3 Extracting Solutions to Defined Situations
380(3)
3.1 Chromosome Structure
381(1)
3.2 Fitness Function
382(1)
3.3 Crossover and Mutation
382(1)
3.4 Selection Algorithm
382(1)
4 Generalizing Using Fuzzy Logic
383(2)
4.1 Fuzzy Sets and Membership Functions
383(2)
4.2 Fuzzy If-Then Rules
385(1)
4.3 Defuzzification
385(1)
5 Experimental Results
385(2)
6 Conclusion
387(1)
7 Future Works
387(1)
References
387(2)
A Study of Map Data Influence on Disaster and Rescue Simulation's Results
389(14)
Kei Sato
Tomoichi Takahashi
1 Introduction
389(1)
2 Agent Based Disaster and Rescue Simulation for Practical Usage
390(2)
2.1 Role of Disaster and Rescue Simulation
390(1)
2.2 RoboCup Rescue Simulation System
391(1)
3 Map Generation from Public GIS Data
392(3)
3.1 Open Source Maps
392(1)
3.2 Creation Simulation Map from Open Source GIS Data
393(2)
4 Simulation Sensitivity of Environments to Simulations
395(6)
4.1 Created Maps from Open Source Data
395(2)
4.2 Sensitivity Analysis of Maps to Simulations
397(1)
4.3 Sensitivity Analysis of Rescue Agents to Simulation Results
398(3)
5 Discussion and Summary
401(1)
References
402(1)
Evaluation of Time Delay of Coping Behaviors with Evacuation Simulator
403(12)
Tomohisa Yamashita
Shunsuke Soeda
Itsuki Noda
1 Introduction
403(1)
2 Evacuation Planning Assist System
404(5)
2.1 Pedestrian Simulator
405(3)
2.2 Prediction System of Indoor Gas Diffusion
408(1)
2.3 Prediction System of Outdoor Gas Diffusion
409(1)
3 Simulation
409(4)
3.1 Simulation Settings
409(3)
3.2 Simulation Result
412(1)
4 Conclusion
413(1)
References
414(1)
Web-Based Sensor Network with Flexible Management by an Agent System
415(10)
Tokihiro Fukatsu
Masayuki Hirafuji
Takuji Kiura
1 Introduction
415(1)
2 Architecture and Function of the Agent System
416(5)
2.1 Basic Function
418(1)
2.2 Rule-Based Function
419(1)
2.3 Distributed Data Processing
420(1)
3 Multi-Agent System
421(1)
4 Discussion and Future Work
422(1)
References
423(2)
Sensor Network Architecture Based on Web and Agent for Long-Term Sustainable Observation in Open Fields
425(10)
Masayuki Hirafuji
Tokihiro Fukatsu
Takuji Kiura
Haoming Hu
Hideo Yoichi
Kei Tanaka
Yugo Miki
Seishi Ninomiya
1 Introduction
425(1)
2 Architecture
426(1)
3 Web Devices for Pure Web
426(2)
4 Experiments Using Field Server
428(2)
5 Results and Discussions
430(2)
6 Conclusions
432(1)
References
433(2)
A Multi-Agent View of the Sensor Web
435(10)
Quan Bai
Siddeswara Mayura Guru
Daniel Smith
Qing Liu
Andrew Terhorst
1 Introduction
435(2)
2 The Sensor Web
437(2)
3 Sensor Webs and Multi-Agent Systems
439(1)
4 Using Multi-Agent Coordination Techniques in Sensor Web
440(2)
4.1 Including Multi-Agent Facilitators in Sensor Web
440(1)
4.2 Building Trust Based on Reputations
441(1)
5 Conclusion and Future Work
442(1)
References
443(2)
Author Index 445
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