IIIA - Artificial Intelligence Research InstituteCSIC – Spanish Council for Scientific Research

Deliverable 2.1: e-Institutions oriented to the use of reputation

Jordi Sabater-MirIsaac PinyolDaniel VillatoroGuifré CuníCarles SierraJuan Antonio RodriguezJosep Lluís Arcos

WP2 – Tools development

IIIA-CSIC

Annex I:

1. Using the tool for e-institutions developed by partner number 4, study and design of the extra elements that are necessary to facilitate and study the use of reputation in an e-institution environment.

2. Development of an alpha version of the e-institution tool for reputation modelling.

3. Help to develop the applications allowing the different experiments described in the rest of workpackages to be run.

Corresponding deliverables list:T0 + 12 (D2.1): e-Institutions oriented to the use of Reputation T0 + 20 (D2.2): e-Institution reputation software

E-Institutions IIIA-CSIC

In human societies, institutions regulate the behaviour of people by enforcing laws, fixing protocols, etc.

Open multiagent systems are populated by autonomous entities and therefore, there is no guarantee about what will be the behaviour of these entities.

An e-institutions is the electronic equivalent of a traditional institution but for virtual environments.

E-Institutions IIIA-CSIC

Some vocabulari:

Role. Standardised patterns of behaviour required by all agents playing part in a given functional relationship.

Dialogic Framework. Ontological elements and communication language (ACL) employed during an agent interaction.

Scene. Agents meetings whose interaction is shaped by a well-defined protocol.

Performative Structure. Complex activities specified as connections among scenes.

Normative rules. Define the consequences of the agent actions within scenes.

E-Institutions IIIA-CSIC

Root

Negotiation

Reputationexchange

Delivery Exit

Agora

Performativestructure

Scenes

Institutional agents

E-Institutions IIIA-CSIC

governor governor

E-Institutions IIIA-CSIC

Using reputation in e-institutions IIIA-CSIC

• Integration of reputation mechanisms in the eI.

• Integration of a cognitive agent architecture in the context of an eI.

• Specification and implementation of a common ontology for reputation.

• Human interface with the eI.

IIIA-CSICIntegration of reputation mechanisms

Centralized reputation (eBay, Sporas...)

Distributed reputation (RepAge, ReGreT...)

E-Institution

Agent

Gov

erno

r Rep.system

E-Institution

Agent

Gov

erno

r

«interface»EInstitutionService

«interface»EInstitutionProfile

ReputationService RepProfile0..*

0..*

Rep.system

eI-service

Using reputation in e-institutions IIIA-CSIC

• Integration of reputation mechanisms in the eI.

• Integration of a cognitive agent architecture in the context of an eI.

• Specification and implementation of a common ontology for reputation.

• Human interface with the eI.

IIIA-CSICEIAgent architecture

API (Governor access )

En

Newmessages

Messages toeInstitution

Messages fromeInstitution

Asynchron CallsAPI (Agent access )

GOVERNOR

EIAGENT

Asynchron Calls

E1SelectTasks

RuningTasks

IIIA-CSICEIAgent architecture

EIAgent GovernorAPI(G) API(A)

Req(A)

Ans(A)

IIIA-CSICJadex architecture

JADEX Agent

E1E2En

Events Queue

Plans

Goals

Beliefs

SelectPlans

New ApplicationEvent

New GoalEvents

NewCondition

Events

Dispatch Goals

Read/Write Facts

GoalConditions

New MessageEvents

NewMessages

IIIA-CSICJadex architecture

JADEX Agent

E1E2En

Events Queue

Plans

Goals

Beliefs

SelectPlans

New ApplicationEvent

New GoalEvents

NewCondition

Events

Dispatch Goals

Read/Write Facts

GoalConditions

New MessageEvents

API (Governor access )

Newmessages

Messages toeInstitution

Messages fromeInstitution

Asynchron CallsAPI (Agent access )

GOVERNOR

Asynchron Calls

Synchronous layer

EID

EJA

DE

X

capability

IIIA-CSICJadex architecture

JADEXAgent GovernorAPIext(G) API(G) API(A)

Req(A)

Ans(A)

IIIA-CSICJadex architecture

JADEXAgent GovernorAPIext(G) API(G) API(A)

Req(A)

Ans(A)

EIAgent GovernorAPI(G) API(A)

Req(A)

Ans(A)

Using reputation in e-institutions IIIA-CSIC

• Integration of reputation mechanisms in the eI.

• Integration of a cognitive agent architecture in the context of an eI.

• Specification and implementation of a common ontology for reputation.

• Human interface with the eI.

CTR1CTR1 CTR1

CTR1

CTR1CTR1 CTR1

CTR1 CTR2CTR2

CTR3CTR3

OK!

???

?

??

The problem

• What if agents using different reputation models are in the same community?

• Different semantics, different representation of evaluations….

Pepe is Good?

Pepe is 0.7?

Pepe is 5?

IIIA-CSIC

• Let’s speak the same language!

CTR1CTR1 CTR2

CTR2

Ontology Mapping for CTR1

Common Reputation Ontology

Ontology Mapping for CTR2

Communication

IIIA-CSIC

The Ontology: Social Evaluation

Evaluation

Target

Strength

Value

Context

Source

Entity

Focus

has

belongs to

Value

[0,1] R

0..1

1

0..1

1

1

belongs to

belongs to

belongs to

Voice

Eval.

Gossiper

Recipient

belongs tohas

0..1

0..1has

belongs to

Norm

Single Agent

Group

Institution

is

Skill

Standardis

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The Ontology: Evaluative Belief

Voice

Voice

has

belongs to

1

Eval.

EvaluationEntity

Entities

has

belongs to belongs to

1..n 1

Eval.

Evaluation Entity

Entities Voice

Voice

IdTransEval.

Real

has has has

belongs to belongs to belongs to belongs to

1 1..n1 1 1

Reputation SharedImage Image DExperience SharedVoice

EvalBelief

SimpleBeliefMetaBelief

is is

is

IIIA-CSIC

Value Representation

Evaluation

Target

Context

Value

Strength

Source

Entity

Focushas

belongs to

[0,1] R

Value

0..1

1

1

1

0..1

belongs to

belongs to

belongs to

Voice

Eval.

Gossiper

Recipient

belongs tohas

0..1

0..1has

belongs to

- Accuracy +

BooleanFalse/True

Discrete Sets{VB, B, N, G, VG}

Probability Distribution

Fuzzy Sets

VB B N G VG0

1

0.5 0.5

00

1

100755025

Value

Bounded Real[0,1]

IIIA-CSIC

Boolean{False,True}

Discrete Sets{VB, B, N, G, VG}

Probability Distribution

VB B N G VG0

1

0.5

Value

Bounded Real[0,1]

Max

Min

go

od

nes

s

False True

Max

Min

go

od

nes

s

VB B N G VG

Max

Min

go

od

nes

s

0 10.5

Boolean Discrete Set

Bounded Real

VB B N G VG0

1

VB B N G VG0

1

Prob. Distribution

Min Max

Semantic of the representations

IIIA-CSIC

Conversions between types

VB B N G VG

Some of them…

X ≥ 0.5

VG 0.9

G 0.7

N 0.5

B 0.3

VB 0.1

[0.8,1) VG

[0.6,0.8) G

[0.4,0.6) N

[0.2,0.4) B

[0,0.2) VB

Prob. Distribution

Discrete Set{VB,B,N,G,VG}

Real[0,1]

Boolean{False,True}

5

1

)12(101)(

iiXiXCM

VB B N G VG

VB B N G VG VB B N G VG

false true

VB VG

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Conversion Uncertainty (CU)

• Uncertainty produced by conversion between representation types.

To

FromBoolean Discrete Set Bounded

RealProb. Dist.

Boolean 0 1.29 5.64 21.19

Discrete Set 0 0 4.32 19.89

Bounded Real

0 0 0 15.55

Prob. Dist 0 0 0 0CU values

• Let X,Y be representation types, then the CU value associated to the conversion from type X to Y is defined as:

CU(X,Y) = H(Y | X)(Conditional entropy)

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Input calls

Output calls

directExp(DExperience)comm(EvalBelief)

getReputation(Entity)ReputationgetReputation(Entity,Focus)ReputationgetImage(Entity,Focus)Image

API Interface

Implementation(1)

DecisionMakingModule

Communication Module

CTRy

APIy

Interface

Interface Interface

Interface

Interface

- Funcionality +

API interface and agent architecture

IIIA-CSIC

Implementation(2)API interface for Abdul-Rahman & Hailes Model

• Distributed Model

• Agents evaluate direct experiences with {VU,U,T,VT}

• Agents can receive recommendations (direct experiences) from others.

• The model returns a degree of trust of agent A in context C with the values{Very Trustworthy, Trustworthy, Untrustworthy, Very Untrustworthy} or with an uncertain value: U+, U0, U- (between VT-T, T-U, U-VU)

• Comm(DExperience)• directExp(DExperience)

• getImage(Entity, Focus) Image

Evaluation: discrete sets {VB,B,G,VG}

1 1 1 11 1 1

VU U T VTU- U0 U+

Evaluation: probability distribution

API Implementation

IIIA-CSIC

Implementation(3)API interface for eBay Model

• Centralized Model

• Users evaluate their transactions sending to the system {+1,0,-1}

• The reputation of a concrete user is a number between 0 and 100.000, represented by a system of colored stars.

API Implementation

• Comm(DExperience)

• getReputation(simpleAgent)Reputation

Evaluation: discrete sets

-1 VB

0 N

+1 VG

Evaluation: bounded real

IIIA-CSIC

Using reputation in e-institutions IIIA-CSIC

• Integration of reputation mechanisms in the eI.

• Integration of a cognitive agent architecture in the context of an eI.

• Specification and implementation of a common ontology for reputation.

• Human interface with the eI.

DB

Tomcat(web server)

DOM

SERVER SIDE

CLIENT SIDE

JavaScript(Script language)

XML(data)

AJAXHuman user

TRACKER

Root

Negotiation

Reputationexchange

Delibery

Exit

Agora

Electronic Institution

E-AgentE-Agent

I-Agent

Governor Governor Governor

SERVLET

StaffAgent

StaffAgent

Trackerdata

Institutionaldata

IIIA-CSIC