MSc Presentation

Personality in Argumentative Agents

Marlon Etheredge

7 November 2016

Utrecht University

Table of Contents

Introduction

Argumentation

Personality

Personality Model

Reasoning

Software Implementation

Opponent Modelling

Conclusion

1

Introduction

Research Topic

• Software agents in argumentation dialogues

• Agents try to settle their differences, which has many

applications including (explaining) decision making [Zho+14],

training humans [Van11] and resolving conflicts in firewalls

[App+12]

• Argumentation can be in the form of deliberation, negotiation

and persuasion among others

• Increasing amount of applications requires adjustability of the

agent according to the application context

• Introducing personality in argumentative agents

2

Argumentation Dialogues

• This research focuses on persuasion dialogues

• Agents need to settle on a conflicting point of view, called the

topic

• As an example, two agents Paul and Otto, can settle their

differences regarding a topic: Science endangers humanity

• Paul, the proponent of the dialogue, starts by claiming the

topic of the dialogue

3

Persuasion

Peter: Science endangers humanity. (Making a claim)

Otto: Why do you think that science endangers humanity?

(Asking for support for the claim)

Peter: Since science brings about many new technologies

that could potentially harm human-beings.

(Providing support for the claim)

Otto: I agree with you that science brings about new

technologies. (Conceding the provided support for

the claim) But I disagree that this poses a threat to

humanity, since science primarily introduces new

technologies that improve the lives of human-beings.

(Providing a counter argument)

4

Peter: Why do you think that these technologies improve

the lives of human-beings? (Asking for support for

the counter argument)

Otto: Since these technologies provide for a method of

helping humans in situations where they would have

been helpless otherwise. In addition, improving the

lives of human-beings does not endanger humanity.

(Providing support for the counter argument)

Peter: OK, I agree that science introduces new technologies

that improve the lives of human-beings. Moreover, I

agree that improving the lives of human-beings does

not endanger humanity. (Conceding a claim)

5

Formalization

• Using Prakken’s dialogue framework [Pra05]

• Using ASPIC+ [Pra10] as a logic for defeasible argumentation

• Different attitudes of argumentative agents are built on top of

Parsons et al. [PWA03]

6

Research Direction

• Previously, reasoning of argumentative agents was primarily

based on game-theoretic approaches

• Personality in the reasoning process of argumentative agents

has not been studied frequently

• Studying the modelling of personalities of opponents of these

argumentative agents

7

Research Topic

• Personality in agents increases the adjustability of the agent’s

reasoning process, according to the context of the application

• By modelling the personality of the opponent, the agent can

include knowledge of the opponent’s personality and thus its

behavior in its reasoning process

• It is expected that personality in agents contributes to the

compatibility of human- and artificial intelligence- tasks

8

Research Topic

• Based on the configuration of the personality, the agent can

behave differently

• In addition, the agent can prefer or disprefer using certain

utterances or only use them under certain conditions

Quick decisions

The agent could be configured to easily accept claims by its

opponent, reaching decisions quicker

Absolute truth

The agent could be configured to only accept arguments when the

opponent uses irrefutable argumentation in scenarios where the

correctness of the outcome of a dialogue is critical

9

Research questions

1. How can personality be introduced to argumentative agents

for persuasion dialogues?

2. How can a model for personality in argumentative agents be

devised that allows argumentative agents to reason according

to a personality configuration?

3. How can an argumentative agent featuring personality be

implemented?

4. How can an argumentative agent featuring personality model

the personality of its opponent?

10

Approach

• Theoretical model of personality in argumentative agents

• Implementation of an argumentative agent featuring

personality based on Erik Kok’s BAIDD framework [Kok13]

• Method for modelling the personality of the opponent

11

Argumentation

Dung’s Abstract Framework

Science endangers

humanity.

Science does not

endanger human-

ity.

New technologies

harm humans.

New technologies

improve lives of

humans, improv-

ing lives does not

harm humans.

• Dung describes a formalism of argumentation [Dun95]

allowing for the description of arguments and attack:

• A set A of arguments

• A binary relation on arguments Def , called attack

• Allowing for different notions of acceptability describing the

status of arguments

• Used to draw conclusions based on AF = (A,Def )

12

Dung’s Abstract Framework

A B C D

• Dung describes a formalism of argumentation [Dun95]

allowing for the description of arguments and attack:

• A set A of arguments

• A binary relation on arguments Def , called attack

• Allowing for different notions of acceptability describing the

status of arguments

• Used to draw conclusions based on AF = (A,Def )

12

ASPIC+

• Argumentation system, instantiation of Dung’s system

• Sound (deductive) and unsound (defeasible) reasoning

• Contrariness function representing contrary relationships like

’harms humans’ and ’saves lives’

• Specification of preference orderings over defeasible inference

rules, arguments and a knowledge base

13

ASPIC+

• Arguments are constructed based on a knowledge base in an

argumentation system (K,≤′)• Strict rules of the form ϕ1, . . . , ϕn → ϕ

• Defeasible rules of the form ϕ1, . . . , ϕn ⇒ ϕ

• E.g. A = ϕ, A is an argument using no rules of inference,

• for rs = ϕ→ ψ, B = ϕ,ϕ ⊃ ψ → ψ, B is an argument using

a strict inference rule rs from which it without exception

follows that ψ,

• for rd = ϕ⇒ γ, C = ϕ,ϕ ⊃ γ ⇒ γ, C is an argument using a

defeasible inference rule rd from which it presumably follows

that γ

14

ASPIC+

• Three types of attack:

• An argument A undercuts an argument B if A attacks an

inference rule of B

• An argument A rebuts an argument B if A attacks the

conclusion of B

• An argument A undermines an argument B if A attacks a

premise of B

• Status of arguments:

• An argument is justified if it can make the opponent run out of

replies

• An argument is overruled if it is not justified and defeated by a

justified argument

• An argument is defensible if it is not justified but none of its

defeaters is justified

15

Prakken’s Abstract Framework

• Has a dialogue goal and at least two participants

• Communication language Lc , defining the available speech

acts

• Protocol Pr , governing the allows speech acts throughout the

dialogue

• Commitments, propositions the participant is expected to

defend publicly

• Effect rules C of speech acts in Lc , describing the effects of

speech acts on the commitments of the participants

• Outcome, turntaking- and termination rules

16

Liberal Dialogue Systems

• Framework specialized for persuasion dialogues

• Specifies a set of protocol rules for persuasion

• Defines a set of speech acts and corresponding effects rules

for persuasion

• Specifies corresponding turntaking-, outcome- and

termination rules

17

Speech Acts for Persuasion

Acts Attacks Surrenders

claim ϕ why ϕ concede ϕ

why ϕ argue A retract ϕ

argue Awhy ϕ(ϕ ∈ prem(A)

argue B(B defeats A)

concede ϕ

(ϕ ∈ prem(A) or ϕ = conc(A))

concede ϕ

retract ϕ

18

Effect Rules for Persuasion

• A participant that claim(ϕ) or concede(ϕ) commits himself to

ϕ

• A participant that retract(ϕ) uncommits himself to ϕ

• A participant that argue A commits himself to the premises of

A and the conclusion of A

19

Example Persuasion Dialogue

P1: claim endangersHumanity

O2: why endangersHumanity

P3: endangersHumanity since harmHumans

O4: why harmHumans

P5: harmHumans since newTechnologies

O6: concede newTechnologies O13: ¬harmHumans since helpingHumans

O7: claim ¬endangersHumanity

P8: why ¬endangersHumanity

O9: ¬endangersHumanity since helpingHumans

P10: why helpingHumans

O11: helpingHumans since newTechnologies

P12: concede helpingHumans

O14: retract endangersHumanity

20

Personality

Personality Theories

• Different stances in how ’personality’ should be investigated

including biological, evolutionary and behaviorist stances

• Personality traits subdivides the concept in measurable

patterns of humans’ behavior

• No consensus on the amount of traits

• Different taxonomies exist varying in the number of

personality traits and the description of them

• Five-factor model [JS99; MC08; Wig96], Eysenck Personality

Inventory [EE65], Myers-Briggs Type Indicator [MM10],

HEXACO [Ash+04]

21

FFM (OCEAN Model)

• Our agent’s personality model is based on the Five-factor

model (FFM)

• Describes the concept of personality in terms of five

personality traits (often referred to by the acronym OCEAN):

• Openness to Experience: Active seeking and appreciation of

experiences for their own sake

• Conscientiousness: Degree of organization, persistence, control

and motivation

• Extraversion: Quantity and intensity of energy directed

outwards into the social world

• Agreeableness: Kinds of interactions an individual prefers from

compassion to tough mindedness

• Neuroticism: Psychological distress

22

FFM (OCEAN Model)

Each personality trait is subdivided in six personality facets

O C E A N

Fantasy Competence Warmth Trust Anxiety

Aesthetics Order Gregariousness Straightforwardness Angry Hostility

Feelings Dutifulness Assertiveness Altruism Depression

Actions Achievement Striving Activity Compliance Self-Consciousness

Ideas Self-Discipline Excitement Seeking Modesty Impulsiveness

Values Deliberation Positive Emotions Tender-Mindedness Vulnerability

23

Personality Model

Personality Model

• Model describing the personality of the argumentative agent

• Divided in three components:

Personality Vector Associates for each personality facet

from the FFM a strength that indicates the

strength of the personality facet in the agent’s

personality

Attitude Acts as a condition that must be met before the

agent is allowed to act in an argumentative

dialogue

Reasoning System Defines, based on the personality of the

agent, the preference of the agent in terms of

speech acts and attitudes

24

Action Selection vs Revision

The personality model makes a distinction between two types of

personality facets and corresponding reasoning:

Action Selection

• Preference ordering over

speech act types

• E.g. an agent prefers

claiming over conceding

Action Revision

• Preference ordering over

attitudes

• E.g. an agent prefers to be

faithful over rigid when

conceding

25

Action Selection vs Revision

Action Selection

• Self-consciousness

• Assertiveness

• Actions

• Ideas

• Values

• Competence

Action Revision

• Achievement Striving

• Self-discipline

• Deliberation

• Activity

• Trust

• Straightforwardness

• Modesty

• Anxiety

• Angry Hostility

• Depression

26

Personality Theory

Some of the personality facets in the FFM are non-beneficial to the

personality model of the argumentative agent:

O C E A N

Fantasy Competence Warmth Trust Anxiety

Aesthetics Order Gregariousness Straightforwardness Angry Hostility

Feelings Dutifulness Assertiveness Altruism Depression

Actions Achievement Striving Activity Compliance Self-Consciousness

Ideas Self-Discipline Excitement Seeking Modesty Impulsiveness

Values Deliberation Positive Emotions Tender-Mindedness Vulnerability

27

Personality Theory

• Each personality trait and corresponding personality facet has

a description in the personality theory

• IPIP [Gol99] contains a comprehensive description of these

based on the NEO PI-R personality inventory [CM92]

• Facets included in our personality model are interpretations of

the descriptions in IPIP tailored to argumentative agents

28

Personality Facets

O C E A N

Actions Competence Assertiveness Trust Anxiety

Ideas Achievement Striving Activity Straightforwardness Angry Hostility

Values Self-Discipline Modesty Depression

Deliberation Self-Consciousness

Self-consciousness: ”Tendency to be shy or anxious”, not

preferring claim and argue, preferring to concede

29

Personality Facets

O C E A N





Assertiveness: ”Social ascendancy and forcefulness of expression”,

preferring claim

29

Personality Facets

O C E A N





Actions: ”Openness to new experiences on a practical level”,

preferring concede

29

Personality Facets

O C E A N





Ideas: ”Intellectual curiosity”, preferring challenge

29

Personality Facets

O C E A N





Values: ”Readiness to re-examine own values and those of

authority figures”, preferring retract

29

Personality Facets

O C E A N





Competence: ”Belief in own self-efficacy”, disfavor retract and

accept, preferring argue

29

Personality Facets

O C E A N





Achievement Striving: ”The need for personal achievement and

sense of direction”, preferring to achieve and defend its goal

30

Personality Facets

O C E A N





Self-discipline: ”One’s capacity to begin tasks and follow through

to completion despite boredom or distractions”, preferring to add

to lines of dispute

30

Personality Facets

O C E A N





Deliberation: ”Tendency to think things through before acting or

speaking”, preferring well-motivated moves

30

Personality Facets

O C E A N





Activity: ”Pace of living”, preferring to move moves in a dialogue

30

Personality Facets

O C E A N





Trust: ”Preference in believing others”, preferring attitudes that

help the agent concede

30

Personality Facets

O C E A N





Straightforwardness: ”The tendency of a person to be direct and

frank in communication with others”, prefer not to be incoherent,

irrelevant or verbose

30

Personality Vector

• Let AS denote the set of action selection personality facets

and AR denote the set of action revision personality facets

• Let Strength(f ) 7→ R denote the strength of facet f with

f ∈ AS or f ∈ AR• An action selection personality vector PVAS is a vector

[Strength(f1), Strength(f2), . . . ,Strength(fn)] Such that

n = |AS| and f1, f2, . . . fn ∈ AS• An action revision personality vector PVAR is a vector

[Strength(f1), Strength(f2), . . . ,Strength(fn)] Such that

n = |AR| and f1, f2, . . . fn ∈ AR

31

Attitudes

• Attitudes specify under what condition an agent is allowed to

make a move containing a certain speech act

• Attitudes are associated with speech act types present in the

framework

• If the condition does not pass, the agent cannot make that

move

• In addition to a preference for certain speech act types, the

agent’s preference specifies preferences for certain attitudes

through action revision

• Attitudes were first introduced by Parsons et al. [PWA03] and

extended in this research

32

Attitudes

Assertion Attitudes

• Confident

• Careful

• Thoughtful

• Spurious

• Deceptive

• Hesitant

33

Attitudes

Acceptance Attitudes

• Credulous

• Cautious

• Skeptical

• Faithful

• Rigid

34

Attitudes

Challenge Attitudes

• Judicial

• Suspicious

• Persistent

• Tentative

• Indifferent

35

Attitudes

Retraction Attitudes

• Regretful

• Sensible

• Retentive

• Incongruous

• Determined

36

Attitudes

Argue Attitudes

• Hopeful

• Dubious

• Thorough

• Misleading

• Fallacious

• Devious

37

Summary

• Agent personality model as personality vector and attitudes

• Based on the FFM personality theory

• Distinction between action selection and action revision

• Model is extensible with more facets and attitudes, additional

or different descriptions and even different personality theories

38

Reasoning

Reasoning

• The agent’s reasoning process is taken care of by the agent’s

reasoning system consisting of two components:

Reasoning Rules Determine according to the strengths of

personality facets an output value used to

compute preference orderings

Reasoning Algorithm Uses these output values to generate

moves that are played by the agent in a dialogue

• The reasoning system makes use of a Mamdani Fuzzy

Inference System (FIS) [MA75] to compute preference values

based on reasoning rules and facets strengths

39

Mamdani Fuzzy Inference System

• Mamdani FIS computes output values based on a set of input

values, a membership distribution and a set of fuzzy rules

• Reasoning rules are implemented as fuzzy rules

• Using three fuzzy classes for input values: Low, Med and High

and two for output values: Favored and Disfavored

• Support for operators like and, or and not respectively

implemented as min(x , y), max(x , y) and 1− x

40

Reasoning Rules

if x is med and y is high then z is disfavored

if a is low and b is med then z is favored

41

Reasoning Rules

• Reasoning rules for action selection and action revision now

can be formalized, for example:

• if ideas is high then challenge is favored

• if deliberation is not high then thoughtful is disfavored

• Reasoning rules introduce a syntax for specifying the effects of

the strengths of facets in the agent’s personality on its

behavior

• Reasoning rules for action selection use strengths specified in

PVAS and output preference values for speech act types

• Reasoning rules for action revision use strengths specified in

PVAR and output preference values for attitudes

42

Reasoning Rules (Example)

Now, (complex) reasoning rules can be created that power the

reasoning system of the agent

43


if actions is high

or selfconsciousness is high

then acceptance is favored

43


if ideas is high

then challenge is favored

43


if assertiveness is high

then assertion is favored

43


if achievementstriving is high

and selfdiscipline is high

and straightforwardness is high

and modesty is low

and anxiety is low

and activity is high

and deliberation is high

then thoughtful is favored

43


By combining all these reasoning rules, the agent’s behavior is

adjustable according to the definition of its personality vectors.

The implementation contains seven action selection reasoning rules

and 54 action revision reasoning rules.

43

Reasoning Algorithm

• Consists of an action selection algorithm:

1. Computes, given the agent’s personality, a preference ordering

over speech act types

2. Returns the preference ordering

44

Reasoning Algorithm

• And an action revision algorithm:

1. Takes an preference ordering over speech act types

2. Computes for each speech act type the preference ordering

over attitudes associated with that speech act type given the

agent’s personality

3. Tests whether the speech act type is allowed in a new move

4. If so, the new move is added to a set of moves that is

contributed to the dialogue

5. Returns the set of moves

44

Summary

• Reasoning rules for the implementation of reasoning according

to description of personality

• A reasoning algorithm for the computation of preference

ordering based on the personality of the agent

• Reasoning system of the agent allowing for introduction of

personality in an argumentative agent

45

Software Implementation

BAIPD

• BAIPD, a modified version of Kok’s testbed BAIDD [Kok13]

for experimentation with software agents in deliberation

dialogues

• BAIPD handles the persuasion dialogue process including

protocol rules, turn taking and requesting the agents to make

moves

• The platform contains an implementation of the

argumentative agent with personality making use of the

Fuzzylite library [Rad14] for an implementation of a FIS

46

Overview

47

Personality Vector

48

Action Selection

49

Action Revision

50

Dialog

51

Summary

• BAIPD, modified version of the BAIDD testbed by Erik Kok,

modified for persuasion (liberation dialogues)

• Implementation of the personality model

• Including reasoning rules and reasoning algorithm

52

Opponent Modelling

Opponent Modelling

Need for knowledge of the opponent

Suppose an agent prefers a faithful attitude. This agent faces a

spurious or deceptive opponent. Even though the agent would

typically concede easily, the agent can incorporate knowledge of its

opponent. If the agent would have a method of modelling the

opponent, the agent would prefer to concede less based on this

context.

53

Reasoning Scheme

• Reasoning scheme eliminating possible attitudes by the

opponent based on modus tollens

• Abduction on possible attitudes prunes the set of possible

attitudes

An agent with a confident attitude can assert any proposition

for which he can construct an argument.

The agent has asserted a proposition (claim), but cannot

construct an argument for the claim.

The confident attitude is not a possible attitude for the claim

move.

54

Pn: claim endangersHumanity

On+1: why endangersHumanity

Pn+2: endangersHumanity since harmHumans

• A : M≤∞ × {P,O} −→ ℘(AT ), with AT as the set of

attitudes

• A(d ,Pn) = {confident, careful, thoughtful}

55

Summary

• Continuously pruning the attitude status based on new moves

added to the dialogue

• Model the attitude statuses of moves in the dialogue using

something like a histogram

• Providing the histogram as input to a learning algorithm for

optimization of the agent’s strategy according to its

personality and its opponent’s personality model

56

Conclusion

Conclusion

How a personality can be introduced to argumentative agents for

persuasion dialogues (research question 1) and how a model for

personality in argumentative agents can be devised that allows

argumentative agents to reason according to a personality

configuration (research question 2):

57

Conclusion

• Using the FFM as a basis for a description of personality

• Defining a personality model as (i) a description of the

personality of an argumentative agent in 15 personality facets

(ii) a personality vector describing the agent’s personality

configuration

57

Conclusion

How an argumentative agent featuring personality can be

implemented (research question 3):

57

Conclusion

• Adjustment of Erik Kok’s BAIDD testbed, introducing BAIPD

• Introducing the reasoning system (i) to describe reasoning

rules that determine the effects on preferences based on the

personality configuration (ii) describing a reasoning algorithm

for reasoning based on the agent’s personality

57

Conclusion

On how an argumentative agent featuring personality can model

the personality of its opponent (research question 4):

57

Conclusion

• Maintaining an opponent modelling based on new moves and

corresponding commitments

• Determination of possible attitudes for moves in the dialogue

• Abduction to eliminate possible attitudes

57

Future Research

• Optimizing strategies of agents

• Extension of this research outside the field of argumentation

theory

• Investigating different theorems like ”a dialogue with two

agents that are achievement-striving increase the length of the

dialogue”

• Extension or adjustment of the personality descriptions in this

research

58

Thank you.

59

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