A Comparative Study of Reasoning Techniques for Service Selection

Open multiagent systems do not provide guarantees about the quality of the service of its providers. This makes it difficult for service consumers to find correct service providers. Many existing approaches share the intuition that service consumers can share their knowledge about service providers to help locate useful service providers. However, representing existing past knowledge and reasoning about this knowledge are two important challenges. A traditional approach for dealing with these challenges is to represent past dealings with ratings and to aggregate the ratings. However, rating-based approaches lack the expressiveness to articulate objective information about service dealings. To enable richer representations, we have developed an objective experience-based approach for service provider selection, in which consumers record their experiences with service providers rather than the overall, subjective ratings for a provider. A consumer’s experience with a service provider is represented using an ontology that can capture subtle details including the context in which the service was requested. When a service consumer decides to share her experiences with a second service consumer, the receiving consumer evaluates the experience using its own context and evaluation criteria. In this work, we tackle the problem of reasoning about the collected experiences. We study different reasoning techniques for consumer agents to use in selecting service providers. We formulate these techniques into agent strategies and examine their strengths and weaknesses through simulations.