Radu Jurca DIP internal workshop, EPFL, 2005 Trust, Reputation and Incentives in Online Environments Radu Jurca, Boi Faltings Artificial Intelligence Laboratory Ecole Polytechnique Fédérale de Lausanne liawww.epfl.ch/People/jurca

Radu Jurca – Slide 2 DIP internal workshop, EPFL, 2005 Overview Trust Reputation Mechanisms Signaling RM Sanctioning RM Other Approaches Incentive Compatibility for probabilistic behavior for strategic behavior Conclusions and Future Work

Radu Jurca – Slide 3 DIP internal workshop, EPFL, 2005 On Trust plays an essential role in our society subjective decision to rely on somebody or something depends on: truster, trustee, and context symmetric relation symmetry can be broken by interaction protocols

Radu Jurca – Slide 4 DIP internal workshop, EPFL, 2005 Trust Establishing Mechanisms security mechanisms institutional interpersonal hierarchical CA’s P2P reputation mechanisms reputation mechanisms

Radu Jurca – Slide 5 DIP internal workshop, EPFL, 2005 On Reputation information support for trusting decisions in online systems, often assumed to be objective information information about past behavior Form of feedback? Feedback aggregation?

Radu Jurca – Slide 6 DIP internal workshop, EPFL, 2005 Role of Reputation informative (signaling) aggregated statistics – overview of capabilities collective intelligence saves search time sanctioning incentives for honest behavior cheating becomes economically unattractive

Radu Jurca – Slide 7 DIP internal workshop, EPFL, 2005 Models of Behavior (for Trustee) Probabilistic behavior fixed probabilities no strategies SIGNALING Reputation Mechanisms Opportunistic behavior economic model utility maximizing behavior SANCTIONING Reputation Mechanism

Radu Jurca – Slide 8 DIP internal workshop, EPFL, 2005 Existing Reputation Mechanisms Trustee Behavior ProbabilisticOpportunistic Type of Reputation Mechanism SignalingSanctioning Tools Social Networks Probabilistic Estimation Game Theory Examples... ?

Radu Jurca – Slide 9 DIP internal workshop, EPFL, 2005 Challenges Correctness Obtain honest reports from RATIONAL trusters resistance to collusion scalable robust against manipulation and failure reliable

Radu Jurca – Slide 10 DIP internal workshop, EPFL, 2005 Overview You have seen: what is trust, reputation types of Reputation Mechanisms You will see: Signaling Reputation Mechanisms Sanctioning Reputation Mechanisms Other Approaches Incentive Compatible RM’s

Radu Jurca DIP internal workshop, EPFL, 2005 Signaling Reputation Mechanisms

Radu Jurca – Slide 12 DIP internal workshop, EPFL, 2005 Social Networks and Probabilistic Estimates T(G|O) = f( T(G|B),T(B|O), T(G|R),T(R|O) ) Type B: C:10% D:90% Type R: C:90% D:10% Reputation Mechanism Seller Group of buyers Reports ? B or R ? O R G B

Radu Jurca DIP internal workshop, EPFL, 2005 Sanctioning Reputation Mechanisms

Radu Jurca – Slide 14 DIP internal workshop, EPFL, 2005 Reputation Mechanism Design Reputation Mechanism Trusting Agent Trusted Agent Mechanism Designer Value of Reputation Semantics of Reputation & Protocol Implementation Reputation Information & Reputation Reports Reputation Information & Reputation Reports RULES Trust Decision Maximize the gain of the Trusting Agent given the available data (i.e. the REPUTATION): - scale the value of the transaction - decide whether or not to trade Reputation has a direct influence on future gains. Value of R: How much more can a Trusted Agent gain by starting with reputation R? Value for a negative or positive feedback report! EFFECTIVE: - the gain obtained from cheating is smaller than the value of a negative report INCENTIVE COMPATIBLE COLLUSION RESISTENCE SCALABLE RELIABLE

Radu Jurca – Slide 15 DIP internal workshop, EPFL, 2005 Dellarocas 2004 one seller, the same good, multiple buyers seller can cooperate or defect binary feedback aggregated into reputation the selling price depends on the reputation the mechanism has a Nash equilibrium such that for every acceptable value of the reputation, there is a unique probability that the seller will cooperate

Radu Jurca – Slide 16 DIP internal workshop, EPFL, 2005 Pro’s and Con’s clear reputation semantics designer can choose the desired outcome complicated to analyze human rationality?

Radu Jurca – Slide 17 DIP internal workshop, EPFL, 2005 Different Approaches instead of having truthful reputation reports, make the trustee truthfully confess his intended quality of service or trustworthiness

Radu Jurca – Slide 18 DIP internal workshop, EPFL, 2005 Dellarocas 2003: Goodwill Hunting One seller sells goods of different quality levels Seller has goodwill Goodwill is updated by the “center” The center modifies the transaction prices in order to compensate the goodwill the mechanism provides week incentives for the seller to announce the true qualities

Radu Jurca – Slide 19 DIP internal workshop, EPFL, 2005 Braynov and Sandholm 2001 the seller announces his trustworthiness and the buyer than sets the quantity of the transaction there exists a function q(t) such that the seller truthfully announces his trustworthiness marginal cost function of the seller needs to be known, and has to satisfy certain properties

Radu Jurca DIP internal workshop, EPFL, 2005 Incentive Compatibility

Radu Jurca – Slide 21 DIP internal workshop, EPFL, 2005 Incentive Compatibility reputation should be shared Reputation = Information => it is not for free no verification authorities or TTP’s. The only source of information = feedback from other agents Reputation Mechanisms have to be Incentive Compatible rational agents will truthfully share the reputation information

Radu Jurca – Slide 22 DIP internal workshop, EPFL, 2005 Incentive Compatibility generating feedback is easy! pay for a report generating TRUE feedback is difficult! different solutions for different classes of behavior (of the Trusted Agent) Probabilistic Behavior Opportunistic Behavior

Radu Jurca – Slide 23 DIP internal workshop, EPFL, 2005 Probabilistic Behavior strong correlation between present and future behavior. incentive compatibility is based on side payments side payments depend on future, unknown reports it is possible to design payment rules which make it in the best interest of the agent to report the truth. (Miller, Resnick, Zeckhauser:2003) (Jurca,Faltings:2003)

Radu Jurca – Slide 24 DIP internal workshop, EPFL, 2005 Miller, Resnick, Zeckhauser:2003 side payments computed by scoring rules scoring rules elicit correct estimates can be used for reputation mechanisms when the trustee has one among a countable set of types E.g. logarithmic scoring rule Pay_i = log(Pr[report_j | announcement_i])

Radu Jurca – Slide 25 DIP internal workshop, EPFL, 2005 Miller, Resnick, Zeckhauser:2003 (2) GB Types Feedback Priors: GB Posteriors if updated with +: Posteriors if updated with -: E[Pay] = Pr[+|+]*log(Pr[+|+]) + Pr[-|+]*log(Pr[-|+]) = Truster perceives “+” and announces “+”: E[Pay] = Pr[+|+]*log(Pr[+|-]) + Pr[-|+]*log(Pr[-|-]) = Truster perceives “+” and announces “-”:

Radu Jurca – Slide 26 DIP internal workshop, EPFL, 2005 Miller, Resnick, Zeckhauser:2003 (3) can be made budget balanced can account for reporting costs precise semantics for reputation  prior probabilities need to be common knowledge.

Radu Jurca – Slide 27 DIP internal workshop, EPFL, 2005 Jurca and Faltings 2003 R-Agents buy and sell reputation information Simple Payment Rule: pay a report about B only if the next report about B has the same value Cryptographic measures make the mechanism reliable and safe.

Radu Jurca – Slide 28 DIP internal workshop, EPFL, 2005 Jurca and Faltings 2003 (2)

Radu Jurca – Slide 29 DIP internal workshop, EPFL, 2005 Jurca and Faltings 2003 (3) no a priori common knowledge required mechanism is trustworthy reputation is tied to identity JADE implementation exists  limited set of acceptable behavior models

Radu Jurca – Slide 30 DIP internal workshop, EPFL, 2005 Opportunistic Behavior agents have the freedom to strategically chose their actions in every transaction EXAMPLE: a seller can “work” hard in the beginning, but then cheats from time to time a buyer who gets cheated does not have the incentive to tell the truth because the next report will most likely be positive future reports are not correlated with the present one => no payment rule can guarantee incentive compatibility

Radu Jurca – Slide 31 DIP internal workshop, EPFL, 2005 Opportunistic Behavior (2) it is possible to have an IC mechanisms when reporting agents have a repeated presence in the market INTUITION: Sellers will not cheat on truthful reporters because it is not economical. A buyer has the incentive to develop a reputation for reporting the truth because she will benefit from cooperative trade in the future. EXAMPLE: a simplified setting in which one hotel can provide or not the promised accommodation quality the occupancy of the hotel depends on its reputation clients can come back to the same hotel

Radu Jurca – Slide 32 DIP internal workshop, EPFL, 2005 “CONFESS” – An IC Mechanism both agents submit feedback DECISION: if Hotel admits having cheated record R- if both agents report positive feedback, record R+ if Hotel reports +, and Client reports -, record R- and fine both agents (Jurca,Faltings:2004) prove that the mechanism is incentive-compatible, and derive an upper bound on the percentage of false reports recorded Hotel Client Negative Report Negative Report Both agents fined Positive Report

Radu Jurca – Slide 33 DIP internal workshop, EPFL, 2005 Future Work collusion resistance reputation mechanisms for opportunistic agents who have different characteristics study the influence of mistakes and irrational behavior robustness and scalability in fully decentralized markets (e.g. P2P environments)