Analyzing Control Trust in Normative Multiagent Systems

1. Analyzing Control Trust in Normative Multiagent Systems Joris Hulstijn1jhulstijn@feweb.vu.nl Yao-Hua Tan1 ytan@feweb.vu.nl Leendert van der Torre2 torre@cwi.nl 1. Vrije Universiteit, Amsterdam 2. CWI, Amsterdam and Delft University of Technology

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

3. normative system trustee $$ trustor How? • Recursive modeling: model the decision making of trustor, taking profiles of trustee, and of a normative system, into account Hulstijn, Tan, van der Torre

4. 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. Hulstijn, Tan, van der Torre

5. 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 Hulstijn, Tan, van der Torre

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

7. Observations < Beliefs Goals Goal Generation Goals Planning & Scheduling Actions 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) Hulstijn, Tan, van der Torre

8. 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 } Hulstijn, Tan, van der Torre

9. 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 Hulstijn, Tan, van der Torre

10. 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: notViol(fraud ,ca) 4. Goal of ib:LC & Viol(fraud ,ca)  law suit sanction 5. Goal of ib: notlaw suit 6. Goal of ca: notlaw suit deter 7. Goal of ca: fraud 7. Goal of ca: fraud Hulstijn, Tan, van der Torre

11. 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. Hulstijn, Tan, van der Torre

12. 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 > notin debt • Profile of buyer:Goal of supplier: not shipping > notin debt • ... no transaction! Hulstijn, Tan, van der Torre

13. 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 ton to pay at evidence of shipping, against a sanction of no delivery. • Supplier is obliged ton to ship at evidence of credit, against a sanction of no payment. • Similar principles apply to E-commerce Hulstijn, Tan, van der Torre

14. 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, • thenormative system will actually detect and sanction violations, and • the trustee prefers to avoid sanctions. Hulstijn, Tan, van der Torre

15. 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. Hulstijn, Tan, van der Torre