Tool for simulating reputation management algorithms in multiagent systems

Efficient service-oriented inter-enterprise collaboration focuses on the business processes of the enterprises and hides the technology differences between them. However, such collaboration induces two main challenges. First, there should be an accessible and functioning infrastructure available for the collaboration. Second, as the growing number of participants can lead to the growing level of misbehaving among them, and thus market deterioration, that is why the parties should have common understanding of the behavior that is appropriate and can be trusted. We focus on the trust relationships between the agents' interactions. Agents make a trust decision before interacting, and this decision among other factors is based on an estimation of another agent's reputation. A reputation management system collects and analyzes interactions experience between agents. Let us call a person, company or any other possible entity whose goal is to build an infrastructure for the interactions between enterprises using one of the trust and reputation management algorithms as an infrastructure builder. For an infrastructure builder it is important to evaluate and compare reputation management systems, choosing one of them based on the evaluation and comparison results. This remains an open question in research. The thesis aims at supporting the decision-making process of this kind. We suggest evaluation criteria for a trust or reputation management systems' evaluation. We implement a generic tool which can plug in a trust or reputation management algorithm and simulate the behavior of the multiagent system where every agent follows the same algorithm. We illustrate the tool's support for some of the suggested evaluation criteria. We provide some recommendations for further development of the generic tool for evaluating and comparing the above-mentioned behavior characteristics of different trust and reputation management algorithms. ACM Computing Classification System (CCS): Human-centered computing → Collaborative and social computing → Collaborative and social computing systems and tools → Reputation systems Computing methodologies → Artificial intelligence → Distributed artificial intelligence → Multi-agent system

Operational Models for Reputation Servers

This paper devises a classification system for reputation systems based on two axes, namely: who performs the evaluation of a subjects reputation, and how the information is collected by the reputation system. This leads to 4 possible operational models for reputation systems, termed the Voting Model, the Opinion Poll Model, the MP Model and the Research Model, each of which is then analyzed. Finally, the paper postulates the inherent trustworthiness of each operational model, and concludes with a hypothesis of how these systems might evolve in the future