Learning to Perceive and Act by Trial and Error
Machine Learning
Models and languages for the interoperability of smart instruments
Automatica (Journal of IFAC)
A methodology and modelling technique for systems of BDI agents
MAAMAW '96 Proceedings of the 7th European workshop on Modelling autonomous agents in a multi-agent world : agents breaking away: agents breaking away
On the identification of agents in the design of production control systems
First international workshop, AOSE 2000 on Agent-oriented software engineering
Function Modeling for an Integrated Framework: A Progress Report
Proceedings of the Eleventh International Florida Artificial Intelligence Research Society Conference
Hi-index | 0.00 |
The use of agent to infer actions from domain specific knowledge has proved to be a successful approach. In this paper, we implement an agent-based system extracting knowledge from ontology-based databases that are embedded in intelligent instruments. As the ontology produces static information on the environment, the emerging behavior results from dependence relations between this information and the functional role of each instrument. Agents are organized in two processing agents. The first of them allows dynamic inference on data meaning. In the second agent, knowledge analysis leads to establish dependence relationships between the basic components of the instruments (i.e., variables and services) and to fire remote modes and external services. In such a way, the local model of the intelligent instrument is dynamically extended with capabilities of any other instrument.