Abstract
An automated negotiation environment, in which agents employ dierent bargaining strategies is described. During negotiation, as more information is exchanged in the negotiation rounds, the agents can change the preferences for certain attributes of the negotiation object. The multi-agent system is developed for a real estate agency business model and several use cases scenarios, using intelligent software agents, are implemented.
Highlights
Negotiation is an important issue in business environments
In our previous works regarding the automated negotiation process, we have proposed bargaining strategies that are based on agent profiles, which can describe statically or can develop dynamically the agent preferences for certain attributes of the negotiation object [5, 6]
This paper extends our previous work and proposes an agent model, in which the agents apply the negotiation strategy best suited to them, according to the negotiation situation
Summary
Negotiation is an important issue in business environments. Automated negotiation is a process, in which software agents communicate between them, in order to reach a mutually acceptable agreement [1]. In our previous works regarding the automated negotiation process, we have proposed bargaining strategies that are based on agent profiles, which can describe statically or can develop dynamically the agent preferences for certain attributes of the negotiation object [5, 6]. The agents in the system use different strategies, for instance, at each negotiation step, the price is decreased by 1, or is decreased by 3 Another strategy rule tells what happens when the price increases with 10% above the private value, if the offer is instantly accepted or not. According to the negotiation history with a certain agent and depending on the cooperation class of the partner, the agent learns in time which negotiation strategy offers the maximum gain. Reject the offers of other agents interested in this object; Table 4.1 The Buyer Agents Requirements and the Seller Offer in the Three-to-One Automated Negotiation Scenario, with Two House Types
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