IEEE Internet Computing
An Information-Theoretic Definition of Similarity
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Learning to match ontologies on the Semantic Web
The VLDB Journal — The International Journal on Very Large Data Bases
Learning to Share Meaning in a Multi-Agent System
Autonomous Agents and Multi-Agent Systems
Ontology-guided learning to improve communication between groups of agents
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
A context-aware approach for service selection using ontologies
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
Argumentation over ontology correspondences in MAS
Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
Engineering self-organizing referral networks for trustworthy service selection
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Dynamic Change Evaluation for Ontology Evolution in the Semantic Web
WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
Deciding agent orientation on ontology mappings
ISWC'10 Proceedings of the 9th international semantic web conference on The semantic web - Volume Part I
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Communication among agents requires a common vocabulary to facilitate successful information exchange. One way to achieve this is to assume the existence of a common ontology among communicating agents. However, this is a strong assumption, because agents may experience situations that result in independent evolution of their ontologies. When this is the case, agents need to form common grounds to enable communication. Accordingly, this paper proposes an approach in which agents can add new service concepts into their service ontologies and teach others services from their ontologies by exchanging service descriptions. This leads to a society of agents with different but overlapping ontologies where mutually accepted services emerge based on agents' exchange of service descriptions. Our simulations of societies show that allowing cooperative evolution of local service ontologies facilitates better representation of agents' needs. Further, through cooperation, not only more useful services emerge over time, but also ontologies of agents having similar service needs become aligned gradually.