Peer-to-peer (P2P) online communities are commonly perceived as an environment offering both opportunities and threats. One way to

The field of peer-to-peer reputation systems has exploded in the last few years. Our goal is to organize existing ideas and work to facilitate system design. We present a taxonomy of reputation system components, their properties, and discuss how user behavior and technical constraints can conflict. In our discussion, we describe research that exemplifies compromises made to deliver a useable, implementable system. Ó 2005 Elsevier B.V. All rights reserved.

Supervised interaction is concerned with the problem of establishing trust between contracting agents in electronic markets. Agents act as representatives of their organisations or of individuals, negotiate contracts for the supply of goods and services and manage their delivery. It is essential for the automation of business transactions to put safeguards in place that ensure that errant behaviour is either prevented or sanctioned. The model proposed in the paper – Supervised Interaction – consists of three elements: an organisational framework, a contract specification language and a contract management protocol. The organisational framework emphasises the importance of introducing a trusted third party into any automated business transaction. Three essential roles are, therefore, proposed: the addressee, counter-party and authority. The normative positions of the agents involved in an automated business transaction are explicitly expressed within the contracts that govern agents’ behaviour during supervised interaction. This interaction model is designed to provide the web of trust necessary for successful deployment of agent-mediated electronic markets.

For distributed systems at large and e-commerce systems in particular, ratings play an increasingly important role. Ratings confer reputation measures about sources. This paper reports our formalization of the rating process. This paper argues that ratings should be context- and individual- dependent quantities. In contrast to existing rating systems in many e-commerce or developer sites, our approach makes use of personalized and contextualized ratings for assessing source reputation. Our approach is based on a Bayesian probabilistic framework.

This paper presents a distributed reputation and trust management framework that addresses the challenges of eliciting, evaluating and propagating reputation for web applications. We propose a broker framework where every service user is associated with a broker who may represent multiple users. A broker collects for its users the distributed reputation ratings about any web service. In return, a user provides its broker the transaction rating after every transaction with any service in order to build up the reputation database on all services. In addition, brokers form a trust network where they exchange and collect reputation data about services. By delegating trust management to brokers, individual users only need to ask their brokers about the reputation of a service before any transaction with a server. The only overhead for a user is the responsibility to share the reputation feedback with its broker. We present the distributed reputation and trust management framework and show the performance of the system by simulations. 1.

Abstract. Today, reputation systems such as ebay’s prominent ”Feedback Forum ” are becoming more widespread. In such a system, reputations are formed by aggregating ratings participants give and receive. These reputations, however, are bound to a specific platform preventing participants from taking and showing their hard-earned reputations elsewhere. That makes the reputations less valuable and leaves them vulnerable to manipulation and total loss. In this paper, we propose a viable solution to these issues in which current P2P and PKI technologies are employed to shift ownership and responsibility back to the participants. Our envisioned Reputation Management System, therefore, uses contextdependent feedback gathered in questionnaires and provides security for peer transactions to ensure integrity, confidentiality and privacy. 1

Using trust and reputation mechanisms offers a promising way to solve the web service selection problem. The investigation of trust and reputation systems in other areas can provide valuable observations and approaches that can be used in web service systems. Therefore, this paper presents a systematic review of various trust and reputation systems and proposes a typology to classify them from three aspects, centralized vs. decentralized, persons/agents vs. resources, global vs. personalized. These aspects are important not only in that they clarify the difference between various existing trust and reputation systems, but also in that they point out the potential research directions for using trust and reputation in web services and provide some reference systems for them.

Abstract. Supervised interaction is concerned with the problem of establishing trust between contracting agents in electronic markets. It is designed to put safeguards in place that ensure that errant behaviour in business transactions is either prevented or sanctioned. Supervised Interaction consists of three elements: an organisational framework, a contract specification language and a contract management protocol. The organisational framework emphasises the importance of introducing a trusted third party into any automated business transaction. The normative positions of the agents involved in an automated business transaction are explicitly expressed within the contracts that govern agents ’ behaviour during supervised interaction. This interaction model is designed to provide the web of trust necessary for successful deployment of agent-mediated electronic markets. 1

Reputation systems offer a viable solution to the old problem of encouraging trustworthy behavior in online communities. Their key presumptions are that the participants of an online community engage in repeated interactions and that the information about their past doings is informative of their future performance and as such will influence it. Thus, collecting, processing, and disseminating the feedback about the participants ’ past behavior is expected to boost their trustworthiness. We investigate and classify the possibilities appeared so far in the literature to do this in the context of P2P networks. We identify three broad classes of approaches: social networks formation, probabilistic estimation techniques and game-theoretic reputation models. They differ greatly in the accompanying trust semantics, mainly reflected in the possibilities offered to the decision makers, and the implementation overhead they incur. The paper bridges the gap between the existing works on trust and reputation management in decentralized networks, driven by the characteristics of the target environment and the formal game-theoretic treatment of reputation, aiming at a clear and analytical decision making. This view leads us to identify the open research issues, oriented towards both efficient and analytical usage of reputation to build trust in P2P networks.

This paper explores delegation decisions predicated on models of trust and autonomy among agents. In socially rich environments, trust and autonomy of artificial agents are key attributes for rational delegation decisions. Social agents are affected by many social attributes such as benevolence, social exchanges, power, and norms. We present cognitively inspired working models of trust and autonomy for delegation among agents that accounts for these social attributes. These models are validated in a simulation of a group of agents who delegate tasks in order to locate the most socially well-suited individuals for performing that task. We define autonomy in such an objective manner that agents who have the highest autonomy with respect to a task will generally be the most socially well suited. Benevolence, social reciprocation, and norms most directly contribute to autonomy and proportionally to social suitability. Derived social power directly contributes to social suitability, whereas independently assigned social power ranking overrides the suitability. We show that trust and autonomy in an agent group changes under various social settings.