Representing and developing knowledge using Jason, CArtAgO and OWL

Risultato della ricerca: Other

3 Citazioni (Scopus)

Abstract

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.
Lingua originaleEnglish
Pagine147-152
Numero di pagine6
Stato di pubblicazionePublished - 2018

Fingerprint

Knowledge representation
Multi agent systems
Ontology
Large scale systems
Semantics

All Science Journal Classification (ASJC) codes

  • Computer Science(all)

Cita questo

@conference{8c3e77b4d13b438d9ede99eac341eb3b,
title = "Representing and developing knowledge using Jason, CArtAgO and OWL",
abstract = "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.",
keywords = "Computer Science (all)",
author = "Francesco Lanza and Antonio Chella and Valeria Seidita",
year = "2018",
language = "English",
pages = "147--152",

}

TY - CONF

T1 - Representing and developing knowledge using Jason, CArtAgO and OWL

AU - Lanza, Francesco

AU - Chella, Antonio

AU - Seidita, Valeria

PY - 2018

Y1 - 2018

N2 - 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.

AB - 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.

KW - Computer Science (all)

UR - http://hdl.handle.net/10447/339862

UR - http://ceur-ws.org/

M3 - Other

SP - 147

EP - 152

ER -