Abstract
We present algorithms for computing definitions and concept descriptions that agents can use to restrict and adapt their knowledge with respect to signature shared with other agents. This ensures that knowledge shared is understood by the communication partners. We focus on agents that make use of description logic ontologies to represent their expertise. We have implemented and evaluated the performance of the algorithms in the form of a case study and on a freely accessible ontology. Our evaluation suggests that definition extraction can reduce the amount of messages exchanged by agents, thus optimising the communication time and effort of the agents.
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Notes
- 1.
Relative to free and accessible occuring ontologies.
- 2.
It is worth noting that this definition of cyclicity is simplified here for brevity. For a more comprehensive description, refer to [10].
- 3.
Higher relative to ANEMONE ontologies.
- 4.
We use the notation \(O, \alpha \) as a shorthand to denote \(O \cup \{\alpha \}\).
- 5.
Symbols not in the signature of the ontology.
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Toluhi, D., Schmidt, R., Parsia, B. (2022). Concept Description and Definition Extraction for the ANEMONE System. In: Alechina, N., Baldoni, M., Logan, B. (eds) Engineering Multi-Agent Systems. EMAS 2021. Lecture Notes in Computer Science(), vol 13190. Springer, Cham. https://doi.org/10.1007/978-3-030-97457-2_20
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