Authors:
Mauricio Paletta
1
and
Pilar Herrero
2
Affiliations:
1
Universidad de Guayana (UNEG), Venezuela
;
2
Universidad Politécnica de Madrid (UPM), Spain
Keyword(s):
Negotiation, Distributed environment, Multi-agent system, Awareness, Artificial neural network.
Related
Ontology
Subjects/Areas/Topics:
Agents
;
Artificial Intelligence
;
Artificial Intelligence and Decision Support Systems
;
Biomedical Engineering
;
Biomedical Signal Processing
;
Computational Intelligence
;
Cooperation and Coordination
;
Distributed and Mobile Software Systems
;
Distributed Problem Solving
;
Enterprise Information Systems
;
Health Engineering and Technology Applications
;
Human-Computer Interaction
;
Knowledge Engineering and Ontology Development
;
Knowledge-Based Systems
;
Methodologies and Methods
;
Multi-Agent Systems
;
Negotiation and Interaction Protocols
;
Neural Networks
;
Neurocomputing
;
Neurotechnology, Electronics and Informatics
;
Pattern Recognition
;
Physiological Computing Systems
;
Sensor Networks
;
Signal Processing
;
Soft Computing
;
Software Engineering
;
Symbolic Systems
;
Theory and Methods
Abstract:
In Collaborative Distributed Environments (CDEs) based on Multi-Agent System (MAS), agents collaborate with each other aiming to achieve a common goal. However, depending on several aspects, like for example the number of nodes in the CDE, the environment condition could be saturated / overloaded making it difficult for agents who are requesting the cooperation of others to carry out its tasks. To deal with this problem, the MAS-based solution should have an appropriate negotiation mechanism between agents. Appropriate means to be efficient in terms of the time involved in the entire process and, of course, that the negotiation is successful. This paper focuses on this problem by presenting a negotiation mechanism (algorithm and protocol) designed to be used in CDEs by means of multi-agent architecture and the awareness concept. This research makes use of a heuristic strategy in order to improve the effectiveness of agents’ communication resources and therefore improve collaboration
in these environments.
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