Formal Analysis of Models for the Dynamics of Trust Based on Experiences
MAAMAW '99 Proceedings of the 9th European Workshop on Modelling Autonomous Agents in a Multi-Agent World: MultiAgent System Engineering
CDS '98 Proceedings of the International Conference on Configurable Distributed Systems
Matchmaking: Distributed Resource Management for High Throughput Computing
HPDC '98 Proceedings of the 7th IEEE International Symposium on High Performance Distributed Computing
A perspective on software agents research
The Knowledge Engineering Review
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Classical approaches to traders in middleware rely on a common language of server, clients, and traders to understand each other. In these systems, pre-defined ontologies play a crucial role. But when dealing with large-scale, open systems such ontologies are no longer available. To cope with this problem, we have developed a radically different approach to trading. Rather than relying 100% on a trader, we assume that traders provide only rough matches and that clients need to make intelligent choices to find a more suited service. To this end, we introduce the notion of trust, which evolves with the client's experience. We implement a simulation of this trust-based trading system and run several test scenarios investigating the use of history and dynamic trust to discover the more suited services. Our analysis and simulation indicate that intelligent clients and rough traders may considerably extend the scope of trading towards large-scale, open distributed systems.