A translation approach to portable ontology specifications
Knowledge Acquisition - Special issue: Current issues in knowledge modeling
Introduction to Multiagent Systems
Introduction to Multiagent Systems
Reputation in Artificial Societies: Social Beliefs for Social Order
Reputation in Artificial Societies: Social Beliefs for Social Order
Social ReGreT, a reputation model based on social relations
ACM SIGecom Exchanges - Chains of commitment
Principles of Trust for MAS: Cognitive Anatomy, Social Importance, and Quantification
ICMAS '98 Proceedings of the 3rd International Conference on Multi Agent Systems
Ontology mapping: the state of the art
The Knowledge Engineering Review
Pellet: A practical OWL-DL reasoner
Web Semantics: Science, Services and Agents on the World Wide Web
An experience on reputation models interoperability based on a functional ontology
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Experiments on semantic interoperability of agent reputation models using the SOARI architecture
Engineering Applications of Artificial Intelligence
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Interaction among agents about reputation is essential to accelerate the convergence of the reputation evaluation. Semantic heterogeneity of different reputation models makes agent interaction a problem, especially in open MAS. We propose in this paper a service oriented architecture, SOARI , to deal with this problem. Namely, SOARI is composed of an external Ontology Mapping Service (OMS ) and an agent internal Translator module. This architecture supports concept mapping and translation among reputation model ontologies to a common ontology and vice-versa, thus allowing heterogeneous agents to interoperate about reputation. We present an example of the OMS 's use, by showing the mapping of two reputation models to a common ontology. Finally, we illustrate the use of the whole SOARI architecture in a simplified electronic commerce scenario. These experiments have enabled us to analyze the limitations and advantages of a hybrid approach for heterogeneous agents interoperation.