Authors:
Guorui Jiang
;
Xiaoyu Hu
and
Xiuzhen Feng
Affiliation:
Beijing University of Technology, China
Keyword(s):
Argumentation-based negotiation, Agent, Selecting arguments, Bayesian learning.
Related
Ontology
Subjects/Areas/Topics:
Agents
;
Artificial Intelligence
;
Computational Intelligence
;
Evolutionary Computing
;
Knowledge Discovery and Information Retrieval
;
Knowledge-Based Systems
;
Machine Learning
;
Negotiation and Interaction Protocols
;
Soft Computing
;
Symbolic Systems
Abstract:
In the Argumentation-based negotiation of agent, it is important to enhance the agent’s ability according to the environment, which would improve the argumentation efficiency significantly. Introducing Bayesian learning model to select arguments in Argumentation-based negotiation, the agent is able to learn and adjust itself according to a dynamic environment. This helps in making more rational and scientific choice for advancing efficiency of argumentation, when it is facing a variety of options for sending arguments. Finally, an example was presented for showing the rationality and validity of the model.