Multi-agent and Complex Systems

481 Pages·2017·1.25 MB·English

by  Quan Bai

Studies in Computational Intelligence 670
Quan Bai
Fenghui Ren
Katsuhide Fujita
Minjie Zhang
Takayuki Ito E ditors
Multi-agent
and Complex
Systems
Studies in Computational Intelligence
Volume 670
Series editor
Janusz Kacprzyk, Polish Academy of Sciences, Warsaw, Poland
e-mail: [email protected]
About this Series
The series “Studies in Computational Intelligence” (SCI) publishes new develop-
mentsandadvancesinthevariousareasofcomputationalintelligence—quicklyand
with a high quality. The intent is to cover the theory, applications, and design
methods of computational intelligence, as embedded in the fields of engineering,
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cellular automata, self-organizing systems, soft computing, fuzzy systems, and
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More information about this series at http://www.springer.com/series/7092
Quan Bai Fenghui Ren
(cid:129)
Katsuhide Fujita Minjie Zhang
(cid:129)
Takayuki Ito
Editors
Multi-agent and Complex
Systems
123
Editors
Quan Bai MinjieZhang
Auckland University of Technology University of Wollongong
Auckland Wollongong, NSW
NewZealand Australia
FenghuiRen Takayuki Ito
University of Wollongong Nagoya Institute of Technology
Wollongong, NSW Nagoya
Australia Japan
Katsuhide Fujita
Tokyo University of Agriculture and
Technology
Koganei,Tokyo
Japan
ISSN 1860-949X ISSN 1860-9503 (electronic)
Studies in Computational Intelligence
ISBN978-981-10-2563-1 ISBN978-981-10-2564-8 (eBook)
DOI 10.1007/978-981-10-2564-8
LibraryofCongressControlNumber:2016951707
©SpringerScience+BusinessMediaSingapore2017
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Preface
Computer-based modelling and simulation have become useful tools to facilitate
understanding of systems in diverse domains such as physics, astrophysics,
chemistry,biology,economics,engineering,andsocialscience.Acomplexsystem
is characterized by a large number of interacting components (e.g. agents and
processes) whose aggregate activities are nonlinear and self-organized. Complex
systems are hard to simulate or model using traditional computational approaches
because of the complex relationships of components and distributed features of
resources and dynamic work environments. Meanwhile, smart systems such as
multi-agentsystemshavedemonstratedadvantagesandgreatpotentialinmodelling
and simulating complex systems.
The International Workshop on Smart Simulation and Modelling for Complex
Systems (SSMCS’15) was held in Buenos Aires, Argentina, in July 2015, and the
InternationalJointAgentsWorkshopandSymposium(IJAWS’15)wasconvenedin
Ishikawa,Japan, inOctober2015.The aimsofSSMCS’15 andIJAWS’15 wereto
bring together researchers in artificial intelligence (AI), agent and multi-agent
systems, and system modelling/simulation to discuss research challenges and
cutting-edgetechniques insmartsimulationandmodelling.Thisbookcontainsthe
extended versions of selected papers from the SSMCS’15 and IJAWS’15 work-
shops. For those workshops we solicited papers on all aspects of smart simulation
and modelling of complex systems through the use of agent and other AI tech-
nologies. They are, for instance, being studied in network modelling, microsimu-
lation modelling, social influence modelling, disaster modelling, environment
modelling, power market modelling and idea-discovery-process modelling. The
goal of the workshops was to gather researchers from these communities to learn
from one another, form long-term collaborations and cross-fertilize the various
disciplines to accelerate progress toward more complex and realistic applications.
v
vi Preface
Finally, we would like to extend our sincere thanks to all authors. This book
would not have been possible without the valuable support and contributions of
those who cooperated with us.
Auckland, New Zealand Quan Bai
Wollongong, Australia Fenghui Ren
Koganei, Japan Katsuhide Fujita
Wollongong, Australia Minjie Zhang
Nagoya, Japan Takayuki Ito
May 2016
Contents
Part I Smart Simulation and Modelling
1 Simulating and Modeling Dual Market Segmentation
Using PSA Framework.. ..... .... .... .... .... .... ..... .... 3
Jiamou Liu, Ziheng Wei and Quan Bai
2 A Multiagent-Based Domain Transportation Approach
for Optimal Resource Allocation in Emergency Management. .... 19
Jihang Zhang, Minjie Zhang, Fenghui Ren and Jiakun Liu
3 CORPNET: Towards a Decision Support System
for Organizational Network Analysis Using Multiplex
Interpersonal Relations.. ..... .... .... .... .... .... ..... .... 33
Jiamou Liu, Anastasia Moskvina and Michael Ouředník
4 Trust Transference on Social Exchanges Among Triads
of Agents Based on Dependence Relations and Reputation ... .... 49
Yunevda E.L. Rojas, Diana F. Adamatti and Gracaliz P. Dimuro
5 Exploiting Vagueness for Multi-agent Consensus.. .... ..... .... 67
Michael Crosscombe and Jonathan Lawry
6 Selecting Robust Strategies Based on Abstracted
Game Models.. .... .... ..... .... .... .... .... .... ..... .... 79
Oscar Veliz and Christopher Kiekintveld
7 Adaptive Forwarder Selection for Distributed Wireless
Sensor Networks ... .... ..... .... .... .... .... .... ..... .... 95
Nor Azimah Khalid and Quan Bai
8 Technical Challenges and Implementation of Mobile Ad-hoc
Water Level Measuring System.... .... .... .... .... ..... .... 109
Takanobu Otsuka, Yoshitaka Torii and Takayuki Ito
vii
viii Contents
Part II Intelligent Agents and Their Applications
9 Membership Function Based Matching Approach
of Buyers and Sellers Through a Broker in Open
E-Marketplace. .... .... ..... .... .... .... .... .... ..... .... 125
Dien Tuan Le, Minjie Zhang and Fenghui Ren
10 Multi-objective Nurse Rerostering Problem .. .... .... ..... .... 139
Shih-Min Wu, Tenda Okimoto, Katsutoshi Hirayama
and Katsumi Inoue
11 Preference Aware Influence Maximization ... .... .... ..... .... 153
Chang Jiang, Weihua Li, Quan Bai and Minjie Zhang
12 Agent-Based Computation of Decomposition Games
with Application in Software Requirements Decomposition... .... 165
Jiamou Liu and Ziheng Wei
13 PreliminaryEstimatingMethodofOpponent’sPreferencesUsing
Simple Weighted Functions for Multi-lateral Closed Multi-issue
Negotiations... .... .... ..... .... .... .... .... .... ..... .... 181
Shinji Kakimoto and Katsuhide Fujita
14 Collective Learning and Information Diffusion
for Efficient Emergence of Social Norms. .... .... .... ..... .... 193
Chao Yu, Zhen Wang, Hongtao Lv, Honglin Bao and Yapeng Li
Part I
Smart Simulation and Modelling