ARGUING FROM EXPERIENCE: Persuasive Dialogue Based on Association Rules.

396 Pages·2010·8.58 MB·English

ARGUING FROM EXPERIENCE:
Persuasive Dialogue Based on Association Rules.
Thesis submitted in accordance with the requirements of the
University of Liverpool for the degree of Doctor in
Philosophy
by
MAYA WARDEH
OCTOBER 2009
A b s t r a c t : “ A r g u i n g f r o m
E x p e r i e n c e ” b y M a y a W a r d e h
The development of autonomous software agents requires consideration of a
number of elements. One interesting aspect of the study of software agency is to
enable effective inductive reasoning, amongst agents, using accumulated
experience of an agent. However, this experience may vary from agent to
another, and only by exploiting these differences, in the right way, can the
agents come to an agreement regarding some issue. This thesis is concerned
with one particular aspect of such agency: modelling the process of arguing
from “experience” to equip autonomous agents (entities) with the capability to
jointly coming to a “view” regarding some case, using the experience they have
independently gathered over time. The background setting for this work deals
with the topic of induction as a dialectical form of reasoning, and attempts to
address some issues regarding its treatment in philosophy, as well as the
problems inherent in the computational modelling of such reasoning. The main
output of the study is a model to enable “Arguing from Experience” which uses
techniques from the field of argumentation theory and knowledge discovery in
databases, to enable agents to pool and construct arguments in support of and
against proposals for “views” regarding some given case. Arguments are pooled
from the agent’s experience by means of Association Rule Mining (ARM)
techniques. The proposed model is intended to describe how “Arguments from
Experience” can be put forward and be systematically attacked in a variety of
ways. This enables the agents to consider all available options and come to a
conclusion about the best “view” to associate with the given case. The
underlying theory extends a well established account from the field of
philosophy, based on the use of argument schemes and critical questions. The
account given is then formalised in terms to enable its representation in agent
systems.
The underlying model has formed the basis for two applications: an
implementation of a dialogue game protocol to provide a proof of concept, as
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Abstract.
well as means to enable automated two-party “Arguing from Experience” for
the purposes of classification; and a framework to aid multiparty “Arguing from
Experience”, intended as means to facilitate argumentation between more than
two parties. Both applications are evaluated using variety of setups in various
domains. The obtained results provided empirical evidence to the efficacy of
“Arguing from Experience”.
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Acknowledgements.
A c k n o w l e d g e m e n t s
This thesis would have not been completed if not for the help I have received
from a number of people whose contribution to my research deserves a special
mention. It is a pleasure to convey my gratitude to them all in this modest
acknowledgement.
In the first place, I am most grateful for the Agha Khan Foundation (AKF) and
Agha Khan Development Network (AKDN) for awarding me their generous
scholarship to pursue my life-dream in studying overseas. Without their support
I would have not been able to finish my research and write this thesis. I would
also like to thank The Department of Computer Science at the University of
Liverpool for providing me with sufficient financial assistance to attend a
number of conferences/workshops and seminars throughout my studying years.
The Department was also the perfect venue, in which I have met many kind
people, who have helped me during the entire course of my studies by providing
me with endless encouragement and constructive feedback. In particular, I
would like to thank Katie Atkinson, Peter Mcburney, Paul Dunne and Michele
Zito. I would also like to thank my fellow PhD students at Liverpool. Above all,
thanks go to the students with whom I shared room 211 during the past three
years, and who had been always there for me when I needed them the most:
Justin Wang, Omar Baquerio Espinosa, Kamal Ali Al-Bashiri, Ji Ruan,
Santhana Chaimontree and Stephanie Chua, to name but a few.
My deepest and most grateful thanks go to my family and friends in Syria. Their
support, trust, encouragement and thoughtfulness have been priceless to me.
My parents, Eman and Ali Wardeh, and my brother Tim, have always been there
for me. I would have not made it today if not for their kind words and their
warm hugs. I cannot express how very grateful I am to the three of them for the
love and support they have given to me, and for all the jasmines they have sent
from Damascus to make my flat smell like home. Great thanks are also due to
my dearest friends Lana Meiqari and Hani Abu-Shaer, who stood by my side
and provided me with invaluable emotional support: They always listened to my
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Acknowledgements.
complaints, justified and unjustified, and provided me with motivation
whenever my self-motivation ran out. I would also like to thank Rob Higgs for
showing interest in my research, and for chatting with me for hours and hours
about the details of this research.
There is also one more person, that I feel most grateful for the everlasting help
he had given me during the past few years, and who has been by my side for the
most part of my PhD studies: my partner George Kidd. I cannot express how
grateful I am for having you in my life. Not only that you have provided me
with home to return to, and a shoulder to cry on every time my research hit a
dead-end. But you also were my anchor, attaching me to reality so I do not get
lost. Your patience, love, warm heart and uniqueness kept me going through the
hardest times, and the coldest winters. George thanks a lot for being there for
me, and hopefully one day I shall be able to return the favour.
Finally, there are two people to whom I am more grateful than words can
convey: my supervisors Frans Coenen and Trevor Bench-Capon. They were the
best supervisors any one could hope for, and more. Their extraordinary
experience, which they happily shared with me, was most invaluable. Their
constructive supervision and their generous feedbacks helped me, more than I
can measure or express, in conducting my research in most efficient way. Their
combined knowledge was the most perfect resource, which inspired me and
enriched my growth, not only as a student but also as a researcher, an
intellectual and a person. Frans, Trevor, I am grateful in every possible way to
you both for your contribution in making me the person that I am today. It has
been a pleasure and an honour to have been supervised by you both.
IV
C o n t e n t s
1: INTRODUCTION ...................................................................................................... 1
1.1. RESEARCH QUESTION ............................................................................................ 2
2.1. RESEARCH DOMAIN ............................................................................................... 3
3.1. THESIS STRUCTURE ............................................................................................... 7
2: LITERATURE REVIEW ........................................................................................ 11
2.1. ARGUMENTATION IN PHILOSOPHY AND AI ..................................................... 11

2.1.1.INDUCTIVE REASONING................................................................................. 12

2.1.2.ARGUMENTATION THEORY .......................................................................... 20

2.1.3.DIALOGUE GAMES FOR ARGUMENTATION ............................................. 33
2.1.4. ARGUMENTATION IN AI ................................................................................. 38

2.1.5.SUMMARY OF ARGUMENTATION IN PHILOSOPHY AND AI ................ 49
2.2. ASSOCIATION RULE MINING AND KNOWLEDGE DISCOVERY...................... 51

2.2.1.THE PROCESS OF KDD ..................................................................................... 52
2.2.2. ASSOCIATION RULE MINING (ARM) ........................................................... 54

2.2.3.SUMMARY OF ARM AND KDD ...................................................................... 67
2.3. CLASSIFICATION IN KDD ..................................................................................... 68

2.3.1.SUMMARY OF THE CLASSIFICATION ALGORITHMS USED ................. 69

2.3.2.ENSEMBLE METHODS ..................................................................................... 73

2.3.3.CLASSIFYING NOISY DATA ........................................................................... 77
2.3.4 SUMMARY OF CLASSIFICATION IN THE FIELD OF KDD ........................ 79
3: A MODEL FOR ARGUING FROM EXPERIENCE ........................................... 81
3.1. A SCHEME FOR ARGUING FROM EXPERIENCE ............................................... 82
3.2. THE DIALOGUE MODEL ...................................................................................... 90
3.2.1. THE SPEECH ACTS ............................................................................................ 91
3.2.2. DISCUSSION ....................................................................................................... 97
3.3. MODEL IMPLEMENTATION USING ARM ........................................................... 98
3.4. GENERAL FRAMEWORK FOR ARGUING FROM EXPERIENCE ..................... 104
3.5. SUMMARY - PROPERTIES OF ARGUING FROM EXPERIENCE ..................... 110
4: THE PADUA PROTOCOL .................................................................................. 113
4.1. PADUA FROM THEORY TO APPLICATION ...................................................... 114
IV
4.1.1.IMPLEMENTATION OF THE PADUA DIALOGUE GAME PROTOCOL. 117

4.1.2. PADUA DIALOGUE EXAMPLE ..................................................................... 120
4.2. STRATEGY AND TACTICS IN PADUA ................................................................ 122

4.2.1.PADUA TACTICS ............................................................................................. 126

4.2.2.DISCUSSION OF SOME EXAMPLE STRATEGIES ..................................... 130

4.2.3.DISCUSSION ..................................................................................................... 133
4.3. ON ACCRUAL OF ARGUMENTS IN PADUA ...................................................... 134
4.4. ARGUING ABOUT INTERMEDIATE CONCEPTS............................................... 138
4.5. SUMMARY ............................................................................................................. 142
5: EMPIRICAL OBSERVATIONS (1) - ANALYSIS OF THE FEATURES OF
THE PADUA PROTOCOL ...................................................................................... 145
5.1. EXPERIMENTAL DESIGN .................................................................................... 146

5.1.1.DATASETS ......................................................................................................... 146

5.1.2.COMPARATOR CLASSIFIERS ....................................................................... 148

5.1.3.EVALUATION MEASUREMENTS ................................................................ 149

5.1.4.METHODOLOGY .............................................................................................. 150
5.2. EVALUATING THE OPERATION OF PADUA ............................................. 151

5.2.1.THE ACCURACY OF THE UNDERLYING DIALOGUES .......................... 151

5.2.2.ASSESSMENT OF NESTED DIALOGUES .................................................... 152

5.2.3.DISCUSSION ABOUT THE LENGTH OF THE DIALOGUES .................... 153
5.3.ASSESSMENT OF PADUA AS A CLASSIFIER ...................................................... 154

5.3.1.COMPARISON WITH OTHER CLASSIFIERS .............................................. 154

5.3.2.ANALYSIS OF APPLYING MCNEMAR’S TEST ......................................... 157
5.4. ASSESSMENT OF PADUA’S ROBUSTNESS TO NOISE ..................................... 159

5.4.1.THE EFFECTS OF RANDOM CLASS NOISE ............................................... 159

5.4.2.MISSING ATTRIBUTES AND THE OPERATION OF PADUA .................. 163
5.5. APPLYING PADUA TO MISINTERPRETED DATA ............................................. 165

5.5.1.ARGUMENT BASED MODERATION OF BENEFIT ASSESSMENT ........ 166

5.5.2. FURTHER DISCUSSION .................................................................................. 172
5.6. ASSESSMENT OF THE ROLE OF STRATEGY IN PADUA ................................. 173
5.7. SUMMARY ............................................................................................................. 176
6: MULTIPARTY ARGUING FROM EXPERIENCE - THE PISA
FRAMEWORK .......................................................................................................... 179
6.1. ISSUES IN MULTIPARTY ARGUING FROM EXPERIENCE .............................. 180
6.2. THE PISA FRAMEWORK ...................................................................................... 184
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6.2.1. THE STRUCTURE OF THE CONTROL LAYER .......................................... 186
6.2.2. TURN TAKING AND TERMINATION POLICIES ....................................... 188
6.2.3. ROLES OF THE PARTICIPANTS ................................................................... 190
6.3. THE ARGUMENTATION TREE ............................................................................ 190
6.3.1. WINNER ANNOUNCEMENT ......................................................................... 193
6.3.2. THE ARGUMENTATION TREE BASIC FUNCTIONS ................................ 194
6.3.3 FICTIONAL EXAMPLE OF THE ARGUMENTATION TREE – EXAMPLE
(1) .............................................................................................................................. 196
6.4. THE CHAIRPERSON ............................................................................................ 199
6.5. SUMMARY OF MULTIPARTY ARGUING FROM EXPERIENCE ....................... 202
6.6. THE IMPLEMENTATION OF PISA AND EXAMPLE DIALOGUE ..................... 204
6.6.1. PISA FRAMEWORK APPLICATION EXAMPLE (1): THE HOUSING
BENEFIT EXAMPLE .................................................................................................. 206
6.6.2. PISA APPLICATION EXAMPLE (2): THE NURSERY EXAMPLE ............ 209
6.7. SUMMARY ............................................................................................................. 214
7: ADVANCED ISSUES IN PISA ............................................................................ 217
7.1. STRATEGY DESING FOR PISA ............................................................................ 217
7.1.1. THREE SUB STRATEGIES FOR THE PISA FRAMEWORK ...................... 222
7.1.2. INTEGRATING THE STRATEGY MODEL IN THE PISA APPLICATION227
7.1.3. EXAMPLE: STRATEGY IN PISA ................................................................... 228
7.1.4. DISCUSSION ..................................................................................................... 237
7.2. GROUPS AND LEADERSHIP IN PISA ................................................................. 239
7.2.1. GROUPS TYPES ................................................................................................ 240
7.2.2. THE ROLE OF THE GROUP LEADER........................................................... 242
7.2.3. GROUPS IN THE PISA APPLICATION ......................................................... 245
7.2.4. DISCUSSION ..................................................................................................... 246
7.3. SUMMARY ............................................................................................................. 247
8: EMPIRICAL OBSERVATIONS (2) - ANALYSIS OF THE FEATURES OF
THE PISA FRAMEWORK ...................................................................................... 249
8.1. EXPERIMENTAL DESIGN ............................................................................ 250

8.1.1. THE INCLUDED DATASETS AND CLASSIFICATION PARADIGMS .... 250

8.1.2.EVALUATION METHODOLOGY .................................................................. 252
8.2. EVALUATING THE OPERATION OF PISA ......................................................... 252

8.2.1.A COMPARATIVE STUDY OF PISA AND PADUA .................................... 254

8.2.2.DISCUSSION ABOUT THE LENGTH OF THE DIALOGUES .................... 257
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8.2.3.DISCUSSION ABOUT THE RELATION BETWEEN THE PARTICIPANTS’

EXPERIENCE AND THE OPERATION OF PISA ................................................... 260
8.3. ASSESSMENT OF PISA AS A CLASSIFIER .......................................................... 261

8.3.1.ANALYSIS OF THE MCNEMAR’S TEST ..................................................... 264

8.3.2.A NOTE ABOUT COMBINING THE PISA WITH A DECISION TREE
CLASSIFIER ................................................................................................................. 267

8.3.3.A COMPARATIVE STUDY OF PISA AS AN ENSEMBLE METHOD ....... 269

8.3.4.CLASSIFYING NOISY DATA ......................................................................... 271
8.4. INVESTIGATING THE ROLE OF GROUPS IN PISA ........................................... 275

8.4.1.SAME NUMBER OF PLAYERS PER GROUP ............................................... 276

8.4.2.VARIABLE NUMBER OF PLAYERS PER GROUP ..................................... 277
8.5. INVESTIGATING THE IMPACT OF PLAYERS’ STRATEGIES UPON
THE OPERATION OF PISA ......................................................................................... 280
8.5.1. SE1 - NO GROUPS ............................................................................................ 282
8.5.2. SE 2–HOMOGENOUS GROUPS ..................................................................... 284

8.5.3.SE 3 – HETEROGENEOUS GROUPS ............................................................. 285
8.6. SUMMARY ............................................................................................................. 286
9: CONCLUSIONS AND FUTURE DIRECTIONS ............................................... 289
9.1. SUMMARY OF CONTRIBUTIONS ....................................................................... 289
9.2. FUTURE DIRECTIONS......................................................................................... 296
BIBLIOGRAPHY ...................................................................................................... 305
A: DESIGN DOCUMENTATION FOR THE JAVA IMPLEMENTATION OF
PADUA ............................................................................................................................. i
A.1 PADUA ANALYSIS AND DESIGN ............................................................................. i
A.2. SIMPLE USER MANUAL FOR PADUA GUI APPLICATION ................................ iv
B: DESIGN DOCUMENTATION FOR THE JAVA IMPLEMENTATION OF
PISA ............................................................................................................................ viii
B.1 PISA ANALYSIS AND DESIGN ...............................................................................viii
B.2. SIMPLE USER MANUAL FOR THE PISA APPLICATION..................................... xi
C: EXTENDING THE ROLE OF THE CHAIRPERSON ...................................... xiv
C.1. LEVEL 2: FOCUSED DIALOGUES ....................................................................... xv
C.2. LEVEL 3: STRICTLY FOCUSED DIALOGUES .................................................... xvi
C.3. DISCUSSION OF THE THREE LEVELS IN PISA ............................................... xvii
VII
C.3. DISCUSSION OF THE THREE LEVELS IN PISA .............................................. xviii
D: APPLYING PISA TO MISINTERPRETED DATA .......................................... xxi
D.1. CROSS VALIDATION USING MISINTERPRETED DATA .................................. xxii
D.2. THE MCNEMAR’S TEST USING MISINTERPRETED DATA ............................ xxiv
D.3. FURTHER DISCUSSION ..................................................................................... xxv
VI II