Interdependence between Agents in Multi Agent Systems

220 Pages·2014·3.48 MB·Dutch

Department of Computing

Interdependence between Agents in Multi Agent Systems

Billy Pik Lik Lau

This thesis is presented for the Degree of
Master of Philosophy (Computer Science)
of
Curtin University

January 2014
Declaration
Declaration

To the best of my knowledge and belief this thesis contains no material previously
published by any other person except where due acknowledgment has been made.

This thesis contains no material which has been accepted for the award of any other
degree or diploma in any university.

Signature : …………………..……
(BILLY PIK LIK LAU)

Date : January 2014
Abstract
Abstract

The interaction between agents can be viewed as a relationship that allows the agents
to exchange information and collaborate to solve a particular problem. The
interdependence relationship between agents leads to a different formation of the
interaction framework called a coalition. Coalition formation (CF) is one of the
fundamental forms of interaction that allows the creation of coherent groups of
agents based on the agents’ relationships. It offers agents the capability of forming a
dynamic and goal-oriented paradigm to achieve their goals effectively. However, it
suffers from major drawbacks such as high communication overhead, limitations of
the protocols and the high computational complexity of the algorithms. In this thesis,
two aspects have been focused, i.e. to improve the cooperation between agents from
the perspective of agents’ interdependence relationship and existing agents’
organization framework.

First, the interdependence relationships between agents based on the dependence
theory have been addressed using the CF. The transitive dependence relationships
between agents is one of our focus since indirect relationships are important for the
agents to depend on each other transitively. We have developed an heuristic based
algorithm that generates the coalitional value using a distributed approach and
calculates the coalition cost given a constraint or budget. It has been shown that the
budget provides a limit to the coalition cost during CF. The coalition earns more
profit since the coalition cost has been reduced. In experiments, the agents’ number
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Abstract
will not exponentially increase the coalition cost. Furthermore, the validity of the
relationships is another research focus as a feasible collaboration will guarantee the
profit of the individual agent in a coalition. It uses the solution derived from the 0-1
Knapsack problem and calculates the relationship based on three different types of
dependence such as and, or and singleton relationships. The experimental results
have shown that a smaller coalition has a higher preservation of the relationships’
validity while conserving the efficiency of the communication rate.

The agents’ organization framework, such as coalition, provides a sophisticated
environment and protocols for agents to depend on each other for solving particular
problems. However, the idle agents are not able maximize its utility because of
certain issues. With this in mind, the join coalition mechanism (JCM) has been
developed to help idle agents increase utility by joining the existing coalition. Two
management approaches have been studied which are macroscopic and microscopic
coalition. The macroscopic coalition is a leaderless coalition that uses the two-phase
evaluation where public voting and trial joining are carried out. The JCM decides the
proposal of idle agents that try to join an existing coalition. Experimental results
based on the macroscopic coalition have shown that idle agents are able to join the
coalition with the communication rate conservation up to 88.00%. We also found out
the behaviour of the agents during the trial joining phase is the key to build trust. The
microscopic coalition has a representative agent that serves as the leader of the
organization. The two-phase joining methods are refined and involves the evaluation
of the coalition leader followed by the weighted voting session by the coalition
member. Experimental results show that increasing the numbers of agents intensify
the competition of voting session from 5.04% to 83.19%. On the other hand, the
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Abstract
increment of the agree evaluation ratio made the chances for the idle agent to join the
coalition raise from 0.00% to 44.36%. The JCM has successfully increased the rate
of cooperation between agents by allowing the idle agents to join the existing
coalition.

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Acknowledgement
Acknowledgement

I would like to express my gratitude to Associate Professor Dr Ashutosh Kumar
Singh and Mr. Terence Tan Peng Lian for their valuable advices and guidance
throughout my research studies (Master of Philosophy, Computer Science). Their
availability for discussion on my research works has further motivated me and I am
truly grateful. Deeply appreciated.

In addition, I would like to thanks the Ministry of Higher Education Malaysia for the
scholarship award entitled “MyBrain 15, MyMaster” and Curtin University Sarawak
Campus for the “Curtin Sarawak Postgraduate Stipend Scholarship Award”. These
financial aids have been a great support for funding my research projects.

My gratitude also goes to my fellow colleagues in Curtin University Sarawak
Campus namely Garenth Lim, Clement Tham, Chua Shin Cheng, Chin Pin Rui and
Arthur Wong for their assists on technical and non-technical support during my
research studies.

All my friends and families deserve a big thank you for their precious support and
encouragement throughout the past two years. In particular, special thanks to my
friend - Sim Sheng Kai for his valuable time in helping me proof-reading the thesis.
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Acknowledgement

Last but not least, I would like to thank God for His guidance throughout my
research studies. He had led me through the hard time and had me prepared
everything required for completing this thesis. All glory and honor goes to Him in
the highest.

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Publications
Publications
JOURNAL PAPERS
1. Billy Pik Lik Lau, Ashutosh Kumar Singh, Terence Peng Lian Tan, "A
Review on Dependence Graph in Social Reasoning Mechanism", Artificial
Intelligence Review, 2012, ISBN: 1573-7462 ,DOI: 10.1007/s10462-012-
9371-x, pp. 1-14 (Published)

2. Billy Pik Lik Lau, Ashutosh Kumar Singh, Terence Peng Lian Tan,
“Forming Transitive Dependence based Coalition utilizing the Concept of
Budget in Multi-agent Systems”, Journal on Artificial Intelligence Tools,
2013 (Under review, ISI indexed).

3. Billy Pik Lik Lau, Ashutosh Kumar Singh, Terence Peng Lian Tan, " Join
Coalition Mechanism for Enhancing Idle Agents’ Utility in a Macroscopic
Coalition" Journal of Artificial Intelligence Research, 2013 (Under review,
ISI indexed).

4. Billy Pik Lik Lau, Ashutosh Kumar Singh, Terence Peng Lian Tan,
“Enhancing Idle Agents’ Utility by Joining an Existing Coalition”, Progress
in Artificial Intelligence, 2014 (Under review, Scopus indexed).

5. Billy Pik Lik Lau, Ashutosh Kumar Singh, Terence Peng Lian Tan, "T-
DepExp: Simulating Transitive Dependence Based Coalition Formation"
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Publications
Pertanika Journal of Science and Technology (JST), 2013 (Under review,
Scopus indexed).

6. Billy Pik Lik Lau, Ashutosh Kumar Singh, Jason Rong Kun Tan, “A
Knapsack based Dependence Relationship Validation Mechanism for
Verifying Agents’ Social Status”, AI & Society, 2014 (Under review, ISI
indexed).

REFEREED CONFERENCE PAPERS
1. Billy Pik Lik Lau, Ashutosh Kumar Singh, Terence Peng Lian Tan,
"Weighted Voting Game based Algorithm for Joining a Microscopic
Coalition", TENCON 2013, Xi'an, China, 2013 (Shortlisted for the best
student paper award) (Published).

2. Ashutosh Kumar Singh, Billy Pik Lik Lau, Terence Peng Lian Tan, "A New
Architecture for Intelligent Agents to Join a Currently Existing Coalition"
Sixth International Conference on Advanced Computational Intelligence
2013, Hang Zhou, China, 2013 (Published).

3. Billy Pik Lik Lau, Ashutosh Kumar Singh, Terence Peng Lian Tan "T-
DepExp: Simulating Transitive Dependence Based Coalition Formation"
Engineering Goes Green, 7th CUTSE Conference, pp. 207-210, Miri, 2012
(Published).
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Table of Contents
Table of Contents
ABSTRACT……. ............................................................................................................ I
ACKNOWLEDGEMENT ............................................................................................... IV
PUBLICATIONS ........................................................................................................... VI
TABLE OF CONTENTS ............................................................................................. VIII
LIST OF FIGURES .................................................................................................... XIII
LIST OF TABLES ...................................................................................................... XVI
ABBREVIATIONS ..................................................................................................... XVII
GLOSSARY…..…... .................................................................................................. XIX
CHAPTER 1 INTRODUCTION ...................................................................................... 1
1.1 RESEARCH CONTRIBUTIONS .................................................................................... 7
1.2 THESIS STRUCTURE ................................................................................................. 8
CHAPTER 2 PRELIMINARIES ................................................................................... 12
2.1 AGENTS’ ARCHITECTURE ...................................................................................... 12
2.2 AGENT’S REPRESENTATION ................................................................................... 13
2.2.1 Root Agent .................................................................................................... 14
2.2.2 Child Agent ................................................................................................... 14
2.2.3 Parent Agent ................................................................................................. 14
2.2.4 Leaf Agent .................................................................................................... 15
2.3 AGENTS’ ROLES .................................................................................................... 15
2.3.1 The Joining Agent ......................................................................................... 15
2.3.2 The Coalition Representative ....................................................................... 18
2.3.3 The Coalition Registration Agent ................................................................. 18
2.3.4 The Coalition Members ................................................................................ 18
2.4 COALITION FORMATION ........................................................................................ 18
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