Authors:
Rodrigo Rodrigues
;
Ricardo Azambuja Silveira
and
Rafael De Santiago
Affiliation:
Federal University of Santa Catarina - PPGCC, Trindade, Florianopolis, Brazil
Keyword(s):
Intelligent Agent, Multi-Context Systems, Symbolic, Connectionist, Negotiation, Information Retrieval.
Abstract:
Nowadays, decisions derived from intelligent systems frequently affect human lives (e.g., medicine, robotics, or finance). Traditionally, these systems can be implemented using symbolic or connectionist methods. Since both methods have crucial limitations in different aspects, integrating these methods represents a relevant step to deploying intelligent systems in real-world scenarios. We start tackling the integration of both methods by exploring how to use different types of information during the agent’s decision-making. We modeled and implemented an intelligent agent based on a Multi-Context System (MCS). MCSs allow the representation of information exchange among heterogeneous sources. We use a framework called Sigon to implement the proposed agent. Sigon is a novel framework that enables the development of MCS agents at a programming language level. As a case study, we present a mediator agent for conflict resolution during negotiation. The mediator agent creates advice by retr
ieving information from the web and employing different data types ( e.g., text and image) during its decision-making. This work provides a promising and flexible way of integrating different information and resources using MCS as the main result.
(More)