A comparative analysis of methodologies for database schema integration
ACM Computing Surveys (CSUR)
KQML as an agent communication language
CIKM '94 Proceedings of the third international conference on Information and knowledge management
Foundations of distributed artificial intelligence
Learning to map between ontologies on the semantic web
Proceedings of the 11th international conference on World Wide Web
PROMPT: Algorithm and Tool for Automated Ontology Merging and Alignment
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
The Chimaera Ontology Environment
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
A survey of approaches to automatic schema matching
The VLDB Journal — The International Journal on Very Large Data Bases
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Traditionally autonomous agents communicate each other using a predefined set of communication primitives implicitly encoded inside the agent protocol. Nowadays, there are various research efforts for automating the deployment of agents in open environments such as Internet. Considering the existence of multiple heterogeneous agents, independently developed and deployed on the Web, the challenge is to achieve interoperability at the communication level, reducing the number of communication errors caused by differences in syntax and semantics of their particular languages implementations. Currently, to support communication interoperability, agent owners must redesign communication syntax and deploy manually their agents, which results in a tedious, time consuming and costly task. To solve this problem we propose an Ontology-based approach for discovering semantic relations between agent communication protocols, which considers the description of primitives and their pragmatics. We present a case study to show the applicability of our approach, and implemented a communication environment to evaluate the resulting set of relations in the Ontology. Results show that our approach reduces the level of heterogeneity among participating agents.