Authors:
Andrew Diniz da Costa
1
;
Carlos J. P. de Lucena
1
;
Viviane T. da Silva
2
and
Paulo Alencar
3
Affiliations:
1
Pontifícia Universidade Católica do Rio de Janeiro, Brazil
;
2
Universidad Complutense de Madrid, Spain
;
3
University of Waterloo, Canada
Keyword(s):
Multi-Agent Systems, Trust, Reputation, Diagnosis, Recommendation.
Related
Ontology
Subjects/Areas/Topics:
Agents
;
Artificial Intelligence
;
Artificial Intelligence and Decision Support Systems
;
Cloud Computing
;
Distributed and Mobile Software Systems
;
e-Business
;
Enterprise Information Systems
;
Internet Technology
;
Knowledge Engineering and Ontology Development
;
Knowledge-Based Systems
;
Mobility
;
Multi-Agent Systems
;
Platforms and Applications
;
Sensor Networks
;
Software Agents and Internet Computing
;
Software Engineering
;
Symbolic Systems
;
Ubiquitous Computing
;
Web Information Systems and Technologies
;
Wireless Information Networks
Abstract:
Open multi-agent systems are societies with autonomous and heterogeneous agents that can work together to achieve similar or different goals. Agents executing in such systems may not be able to achieve their goals due to failures during system execution. This paper’s main goals are to understand why such failures occurred and what can be done to remediate the problem. The distributed, dynamic and open nature of multi-agent systems calls for a new form of failure handling approach to address its unique requirements, which involves both diagnosing specific failures and recommending alternative plans for successful agent execution and goal attainment. In this paper, we discuss solutions to the main challenges of creating a system that can perform diagnoses and provide recommendations about agent executions to support goal attainment, and propose a hybrid
diagnostic-recommendation framework that provides support for methods to address such challenges.