Abstract
This work is primarily based on the use of software agents for automated negotiation. We present in this paper a test-bed for agents in an electronic marketplace, through which we simulated different scenarios allowing us to evaluate different agents’ negotiation behaviours. The system follows a multi-party and multi-issue negotiation approach. We tested the system by comparing the performance of agents that use multiple tactics with ones that include learning capabilities based on a specific kind of Reinforcement Learning technique. First experiments showed that the adaptive agents tend to win deals over their competitors as their experience increases.
The work of Henrique Lopes Cardoso has been funded by a scholarship from Subprograma Ciência e Tecnologia do 2° Quadro Comunitário de Apoio.
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© 1999 Springer-Verlag Berlin Heidelberg
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Cardoso, H.L., Schaefer, M., Oliveira, E. (1999). A Multi-agent System for Electronic Commerce Including Adaptive Strategic Behaviours. In: Barahona, P., Alferes, J.J. (eds) Progress in Artificial Intelligence. EPIA 1999. Lecture Notes in Computer Science(), vol 1695. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48159-1_18
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DOI: https://doi.org/10.1007/3-540-48159-1_18
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