Title :
Multi-issue Automated Negotiation with Different Strategies for a Car Dealer Business Scenario
Author_Institution :
Comput. Sci. Dept., Univ. Politeh. of Bucharest, Bucharest, Romania
Abstract :
The article presents a multi-agent system used for automated negotiation. Different bargaining strategies are used by agents. Machine learning techniques enhance the agents´ behavior during negotiation. The negotiation model, based on the BDI paradigm, is tested in a business scenario involving a car dealer.
Keywords :
automobiles; electronic commerce; learning (artificial intelligence); multi-agent systems; bargaining strategy; car dealer business; electronic commerce; machine learning technique; multiagent system; multiissue automated negotiation; Adaptation models; Computational modeling; Contracts; Multi-agent systems; Proposals; Protocols; Q-learning; automated negotiation; multi-agent systems; strategies;
Conference_Titel :
Control Systems and Computer Science (CSCS), 2015 20th International Conference on
Conference_Location :
Bucharest
Print_ISBN :
978-1-4799-1779-2
DOI :
10.1109/CSCS.2015.53
