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Analyzing Control Trust in Normative Multiagent Systems Joris Hulstijn 1 Yao-Hua Tan 1 Leendert van der Torre 2.

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Presentation on theme: "Analyzing Control Trust in Normative Multiagent Systems Joris Hulstijn 1 Yao-Hua Tan 1 Leendert van der Torre 2."— Presentation transcript:

1 Analyzing Control Trust in Normative Multiagent Systems Joris Hulstijn 1 Yao-Hua Tan 1 Leendert van der Torre 2 1. Vrije Universiteit, Amsterdam 2. CWI, Amsterdam and Delft University of Technology

2 Bled'05Hulstijn, Tan, van der Torre2 Transaction Trust (Tan & Thoen 2000, 2002) 1.How can we model control trust? 2.How does control trust affect transaction trust? Transaction Trust Trust in other Party Trust in control mechanisms Potential Gain Risk & Risk Attitude Personal Relationship Role-based Reputation Trust in institution Understanding control mechanism extern intern

3 Bled'05Hulstijn, Tan, van der Torre3 How? Recursive modeling: model the decision making of trustor, taking profiles of trustee, and of a normative system, into account trustor trustee $$ normative system

4 Bled'05Hulstijn, Tan, van der Torre4 Normative Multiagent Systems (Jones & Carmo 2002) Normative Multiagent Systems are –sets of agents, –whose interaction can be regarded as norm governed. –Norms describe an ideal situation, –but actual situations can deviate from the ideal (violations). Model normative system n, as an agent.

5 Bled'05Hulstijn, Tan, van der Torre5 Overview Case: Letter of Credit –international trade similar to E-commerce Normative MultiAgent Systems –beliefs and goals –constitutive and regulative norms Analysis –contrast situation with and without control

6 Bled'05Hulstijn, Tan, van der Torre6 Case: Letter of Credit (Bons 1997, Lee 2000, Kartseva et al 2004) 1.lack of trust replaced by banking relation 2.evidentairy documents, guaranteed by UN. customer supplier carrier issuing bank corresp. bank 1. Sales contract 2. credit appl. 3. credit 4. credit notif. 5. goods 6. shipping docs 7. shipping docs 8. payment 9. shipping docs 10. payment 11. arrival notif 12. payment 13. shipping docs 14. shipping docs 15. goods

7 Bled'05Hulstijn, Tan, van der Torre7 NMAS 1: Beliefs and Goals Focus on goal generation Production rules A  B represent beliefs and goals, with a priority order <. Belief rules: current state Goal rules: desired state (through actions) < Beliefs Goals Observations Actions Goals Goal Generation Planning & Scheduling

8 Bled'05Hulstijn, Tan, van der Torre8 NMAS 1: Beliefs and Goals Example Belief:at party Goal 1:at party  smoke Goal 2:not smoke Priority: Belief > Goal 1 > Goal 2 Priority: Belief > Goal 2 > Goal 1 Outcome: { at party, smoke } Outcome: { at party, not smoke }

9 Bled'05Hulstijn, Tan, van der Torre9 NMAS 2: Constitutive Norms (Searle 1995) Constitutive norms are used to model the evidentiary documents. For all a: x counts as y in context C. For all a : shipping docs and no shipping counts as fraud in the context of LC. Belief of a: LC & (shipping docs & not shipping)  fraud

10 Bled'05Hulstijn, Tan, van der Torre10 NMAS 3: Regulative Norms (Boella and van der Torre 2004) “Your wish is my command” Agent a is obliged to n to do x in context C, against a sanction s. Carrier is obliged to issuing bank that no fraud occurs in the context of LC, against the sanction of a law suit: 1. Goal of ib: LC  not fraud 2. Goal of ib: LC & fraud  Viol(fraud,ca) detect 3. Goal of ib: not Viol(fraud,ca) 4. Goal of ib: LC & Viol(fraud,ca)  law suit sanction 5. Goal of ib: not law suit 6. Goal of ca: not law suitdeter 7. Goal of ca: fraud

11 Bled'05Hulstijn, Tan, van der Torre11 NMAS 3: Regulative Norms Customer’s profile: ca’s profile of ib: goal 1-5, ca: goal 6, 7 { LC, fraud, not law_suit }. ca’s profile of ib: goal 2 > goal 3 (detect) { LC, fraud, not law_suit, Viol(fraud,ca) }. ca’s profile of ib: goal 4 > goal 5 (sanction) {LC, fraud, not law_suit, Viol(fraud,ca), law_suit} Conflict, resolve by ca: goal 7 > goal 6 { LC, fraud, Viol(fraud, ca), law_suit } But if ca: goal 6 > goal 7 (deter) { LC, not law_suit } So customer will trust carrier, if detect, sanction and deter hold.

12 Bled'05Hulstijn, Tan, van der Torre12 Analysis 1: No Letter of Credit In the absence of party trust and controls –Customer is obliged to supplier to pay at shipping, against an ‘internal sanction’ of being in debt. –Supplier is obliged to customer to ship at payment, against an ‘internal sanction’ of being in debt. –Profile of supplier: Goal of customer: not payment > not in debt –Profile of buyer: Goal of supplier: not shipping > not in debt... no transaction!

13 Bled'05Hulstijn, Tan, van der Torre13 Analysis 2: With Letter of Credit Direct Transaction (same time, location) –Customer is obliged to supplier to pay at shipping, against a ‘sanction’ of no shipping. –Supplier is obliged to customer to ship at payment, against a ‘sanction’ of no payment. Indirect Transaction (distant in time, location) –Customer is obliged to n to pay at evidence of shipping, against a sanction of no delivery. –Supplier is obliged to n to ship at evidence of credit, against a sanction of no payment. Similar principles apply to E-commerce

14 Bled'05Hulstijn, Tan, van der Torre14 Conclusions Model control trust by –regulative norms, seen as violation detection and sanctioning goals of a normative system, –constitutive norms for evidentiary documents. Control trust affects transaction trust, when in the trustor's profile of the trustee, –the normative system will actually detect and sanction violations, and –the trustee prefers to avoid sanctions.

15 Bled'05Hulstijn, Tan, van der Torre15 Conclusions To design control mechanisms for E-commerce –Use standards for evidentiary documents, maintained by an institution that has the power to apply credible sanctions. –Start with a mutual obligation (direct transaction), in which the sanction for one party is non-compliance of the other party. –Create a causal chain (indirect transaction) in which evidence of compliance can replace compliance.


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