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Argumentation-Based Decision Making and Structural Models of Personality Pietro Baroni and Federico Cerutti and Massimiliano Giacomin and Giovanni Guida Dipartimento di Ingegneria dell’Informazione, Universit`a di Brescia Via Branze 38, I-25123 Brescia, Italy December 3, 2010 ARGAIP 2010 c 2010 Federico Cerutti <[email protected]>

Cerutti--ARGAIP 2010

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Page 1: Cerutti--ARGAIP 2010

Argumentation-Based Decision Making andStructural Models of Personality

Pietro Baroni and Federico Cerutti and MassimilianoGiacomin and Giovanni Guida

Dipartimento di Ingegneria dell’Informazione, Universita di BresciaVia Branze 38, I-25123 Brescia, Italy

December 3, 2010

ARGAIP 2010

c© 2010 Federico Cerutti <[email protected]>

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“Good Advice”

The advice should be presented in a form which can be readilyunderstood by decision makers

There should be ready access to both information and reasoningunderpinning the advice

If decision support involves details which are unusual to thedecision maker, it is of primary importance that s/he can discussthese details with his advisor [Girle et al., 2003]

c© 2010 Federico Cerutti <[email protected]> December 2010 2

Practical Reasoning about “What to do”

Knowledge Representation Computation of Outcomes

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Knowledge RepresentationComputation of Outcomes

Conclusions and Future works

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Argument (and Attack) schemes

Argument schemes for knowledge representation [Walton, 1996]

Structure which contains the information supporting a givenconclusion

Modelling conflicts by “attack scheme”

Structure which contains the information supporting a givenconflict

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The main concepts

Circumstance: a state of the world

Fact: a particular circumstance assumed to be true

Goal: a state of the world we want to achieve

Action: support for the achievement of a goal

Emotion: “a strong feeling deriving from one’s circumstances,[or] mood[. . . ]”

Preference: “[. . . ] a greater liking for one alternative overanother or others [. . . ]”

Value: “Worth or worthiness [. . . ] in respect of rank or personalqualities”

Must Value: a value that we are committed to promote

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A scenario (1)

I have to go to theAmazon Rainforest

I want to help people!

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A scenario (2)

Ough! My Hernia! Doc! What canI do?

You can:1) Do a discectomy surgery2) Have a long non-invasive treatment3) Take analgesics

Mmmmhh:1) I promote my safety2) I promote my safety3) I promote charity because I can go to Brazil

Let us assume that these actions are mutually exclusive

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A scenario (2): practical arguments

A2: circumstance: in my situation,action: discectomy surgery,goal: reducing disc herniation,value: safety,sign: +.

[Greenwood et al., 2003]

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Mumble

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A scenario (2): practical arguments

α [PAtS1]: source: A1,target: A2,conditions: A1.action and A2.actionare incompatible.

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A scenario (2): values arguments

V1: value: charity.V2: value: safety.

They are “socially accepted values”.

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A scenario (2): values defence (i)

β [VDes1]: source: V2,target: α,conditions: α.target.value = V2.value andα.source.value 6= A2.value.

Each value is committed to protect each practicalargument that promotes it! And. . .

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A scenario (2): values defence (ii)

γ [VDes2]: source: V1,target: β,conditions: β.source 6= V1 andβ.target.source.value 6= V1.value.

Each value is committed to protect each attackgrounded on each practical argument that promotes it!

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A scenario (2): values defence (ii)

β [VDefence]: defending: A2,defended: V2,conditions: defending.value =defended.value and defended.sign = +.

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A scenario (2): values defence (ii)

γ [VDefence]: defending: A1,defended: V1,conditions: defending.value =defended.value and defended.sign = +.

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A scenario (3)

But I can't do a discetomysurgery since I have a historyof anaesthesia allergy

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A scenario (3): contradictory pract. arg. (i)

A4: circumstance: alternative anaesthesia not availablefor discectomy,action: not discectomy surgery,goal: risk of shock,value: safety,sign: −.

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A scenario (3): contradictory pract. arg. (i)

δ [PAtS2]: source: A4,target: A2,conditions: A4.action = ¬ A2.action.

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A scenario (3): contradictory pract. arg. (ii)

ε [VAAtS]: source: A4,target: β,conditions: A4.action = ¬ β.defended.actionand A4.value = β.defended.value andA4.sign = − and β.defended.sign = +.

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A scenario (4)

But I can't do a discetomysurgery since I have a historyof anaesthesia allergy

Don't worry... There is a kindof anaesthesia you are not allergic to

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A scenario (4): factual arguments

A5: circumstances: alternative anaesthesia is availablefor discectomy.

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A scenario (4): factual arguments

ι [FAtS1]: source: A5,target: A4,conditions: A5.circumstances =¬ A4.circumstances.

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A scenario (5)

OK. With surgery I will getover my illness in very fewdays. But I'm frightened by surgery...

Noo... I categorically rejectthe idea!

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A scenario (5): preferences. . .

P1: preferred: A2,notpreferred: A3.

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A scenario (5): preferences. . .

λ [PRAtS]: source: P1,target: κ,conditions: P1.preferred = κ.targetand P1.notpreferred = κ.source.

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A scenario (5): . . . and emotions

E1: emotion: surgery frightening.

Are emotions rational?

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A scenario (5): . . . and emotions

µ [EAtS1]: source: E1,target: A2,conditions: e(E1,A2) = −.

with e(E1,A2) = −

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A scenario (6)

OK. I must care about my health.Then, I will help people again!

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A scenario (6): Must Value

MUST V2: value: safety.

This is again a rational choice!

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A scenario (6): Must Value

ν [MAtS2]: source: MUST V2,target: γ,conditions: MUST V2.value =γ.target.source.value andMUST V2.value 6= γ.source.value.

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Why three boxes?

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Why three boxes?

1 The set of arguments that take into accountvalues;VAS arguments.

2 The set of arguments whose bases are not rational;EAS arguments.

3 The set of arguments that deal with both facts and values;FAS, PAS, PRAS, and MAS.

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Look familiar?

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Look familiar?

1 The Superego strives to act in a socially appropriate manner.

2 The Id is the innate part of our personality and is based on thepleasure principle.

3 The Ego represents what may becalled reason and common senseand has to conciliate the innateinstincts and the social constraints.

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Knowledge Representation

Computation of OutcomesConclusions and Future works

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Argumentation Framework for Decision SupportProblemAn Argumentation Framework for Decision Support Problem(AFDSP ) is a 12-ple 〈APAS , APRAS , AEAS , AV AS , AFAS ,AMAS ,RPAS , RPRAS , REAS , RV AS , RFAS , RMAS〉 s.t.:

APAS is a set of instances of PAS;

APRAS is a set of instances of PRAS;

AEAS is the set of instances of EAS;

AV AS is a set of instances of VAS;

AFAS is a set of instances of FAS;

AMAS is a set of instances of MAS;

RPAS is a set of instances of PAtS1 and PAtS2;

RPRAS is a set of instances of PRAtS;

REAS is a set of instances of EAtS1 and EDefence;

RV AS is a set of instances of VAtS, VDeS1, VDeS2, VAAtS;

RFAS is a set of instances of FAtS;

RMAS is a set of instances of MAtS1, and MAtS2.

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Argumentation Framework with RecursiveAttacks (AFRA)

An Argumentation Framework with Recursive Attacks (AFRA) is apair 〈A,R〉 where A is a set of arguments and R is a set of attacks,namely pairs (A,X ) s.t. A ∈ A and (X ∈ R or X ∈ A).

Given an attack α = (A,X ) ∈ R, we will say that A is the source ofα, denoted as src(α) = A and X is the target of α, denoted astrg(α) = X . [Baroni et al., 2009b]

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From AFDSP to AFRA

The instances of argument schemes in AFDSP compose the set ofarguments in AFRA and the instances of attack schemes in AFDSPgive rise to the attack relation in AFRA.

Let Φ = 〈APAS , APRAS , AEAS , AV AS , AFAS , AMAS ,RPAS , RPRAS ,REAS , RV AS , RFAS , RMAS〉 be an AFDSP , the correspondingAFRA is defined as Γ = 〈A,R〉 s.t.

A = APAS ∪ APRAS ∪ AEAS ∪ AV AS ∪ AFAS ∪ AMAS ; and

R = RPAS ∪RPRAS ∪REAS ∪RV AS ∪RFAS ∪RMAS .

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Defeat relation

Definition (Direct Defeat)

Let 〈A,R〉 be an AFRA, V ∈ R, W ∈ A∪R, then V directly defeatsW iff W = trg(V ).

Definition (Indirect Defeat)

Let 〈A,R〉 be an AFRA, V ∈ R, W ∈ A, if V directly defeats Wthen ∀α ∈ R s.t. src(α) = W , V indirectly defeats α.

Definition (Defeat)

Let 〈A,R〉 be an AFRA, V ∈ R, W ∈ A ∪R, then V defeats W ,denoted as V →R W , iff V directly or indirectly defeats W .

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Semantics notions

Definition (Conflict–free)

Let 〈A,R〉 be an AFRA, S ⊆ A∪R is conflict–free iff @V ,W ∈ S s.t.V →R W .

Definition (Acceptability)

Let 〈A,R〉 be an AFRA, S ⊆ A ∪R, W ∈ A ∪R, W is acceptablew.r.t. S iff ∀Z ∈ R s.t. Z →R W ∃V ∈ S s.t. V →R Z .

Definition (Admissible set)

Let 〈A,R〉 be an AFRA, S ⊆ A∪R is admissible iff it is conflict–freeand each element of S is acceptable w.r.t. S.

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Preferred Extension

A preferred extension is a maximal (w.r.t. set inclusion) admissibleset.

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Recalling the example. . .

A1

A2 A3A4

V2

V1

d

a

b

g

e

A5

iP1

E1

k l

m MUSTV2

n

Ego

Superego

Id

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. . . and the preferred extension

A3

V2

V1

b

A5

iP1

E1

l

m MUSTV2

n

Ego

Superego

Id

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Knowledge Representation

Computation of Outcomes

Conclusions and Futureworks

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Conclusions

Extension of a previous proposal [Baroni et al., 2009a]

Human emotions in decision making process

Main contribution: preliminary description of a mapping betweenargumentation based decision process and Freud’s three entitiesmodel of personality

c© 2010 Federico Cerutti <[email protected]> December 2010 34

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Future works

Fill the gap between attack schemes and critical questions

Deep analysis on Superego and Id:

Enhancing the relevant argument schemesMore articulated personality models

c© 2010 Federico Cerutti <[email protected]> December 2010 35

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Thank you

c© 2010 Federico Cerutti <[email protected]>

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References

[Baroni et al., 2009a] Baroni, P., Cerutti, F., Giacomin, M., andGuida, G. (2009a).An argumentation-based approach to modeling decision supportcontexts with what-if capabilities.In AAAI Fall Symposium. Technical Report SS-09-06, pages 2–7.AAAI Press.

[Baroni et al., 2009b] Baroni, P., Cerutti, F., Giacomin, M., andGuida, G. (2009b).Encompassing attacks to attacks in abstract argumentationframeworks.In Proc. of ECSQARU 2009, pages 83–94, Verona, I.

[Girle et al., 2003] Girle, R., Hitchcock, D. L., McBurney, P., andVerheij, B. (2003).Decision support for practical reasoning: A theoretical andcomputational perspective.In Reed, C. and Norman, T. J., editors, Argumentation Machines.New Frontiers in Argument and Computation, pages 55–84. Kluwer.

[Greenwood et al., 2003] Greenwood, K., Capon, T. B., andMcBurney, P. (2003).Towards a computational account of persuasion in law.In Proc. of ICAIL ’03, pages 22–31.

[Walton, 1996] Walton, D. N. (1996).Argumentation Schemes for Presumptive Reasoning.Lawrence Erlbaum Associates.

c© 2010 Federico Cerutti <[email protected]> December 2010 37