EPIA 1999: Progress in Artificial Intelligence pp 252-266 | Cite as
A Multi-agent System for Electronic Commerce Including Adaptive Strategic Behaviours
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.
Keywords
Electronic Commerce Weighted Combination Negotiation Protocol Negotiation Model Seller AgentPreview
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