Contexts where agents and humans are required to collaborate and cooperate in a human-like fashion are complex systems where a high degree of self-adaptability of every component is demanding. A fundamental ingredient when developing and implementing this kind of systems is the knowledge representation. Knowledge of the goals, the environment, other agents' capabilities and task and of itself, is crucial in deciding which action to perform to reach an objective and to behave in a self-adaptive way. The problem of knowledge modeling and representation becomes more and more urgent if the agents' operation domain changes at runtime. Knowledge has to be updated and handled while the system is in execution. In this paper, we present a way for implementing a controlled semantic system to manage the belief base of a multi-agent system at runtime. Our work is based on the development of a specific approach for interfacing Jason, CArtAgO and Jena; the knowledge base representation employs OWL Ontology.
Chella, A., Lanza, F., & Seidita, V. (2018). Representing and developing knowledge using Jason, CArtAgO and OWL. In CEUR Workshop Proceedings (pp.147-152). CEUR-WS.
|Autori:||Chella, A.; Lanza, F.; Seidita, V.|
|Titolo:||Representing and developing knowledge using Jason, CArtAgO and OWL|
|Nome del convegno:||19th Workshop "From Objects to Agents", WOA 2018|
|Luogo del convegno:||ita|
|Anno del convegno:||2018|
|Data di pubblicazione:||2018|
|Numero di pagine:||6|
|Citazione:||Chella, A., Lanza, F., & Seidita, V. (2018). Representing and developing knowledge using Jason, CArtAgO and OWL. In CEUR Workshop Proceedings (pp.147-152). CEUR-WS.|
|Tipologia:||0 - Proceedings (TIPOLOGIA NON ATTIVA)|
|Appare nelle tipologie:||0 - Proceedings (TIPOLOGIA NON ATTIVA)|