Preference Based Automated Negotiation for Service Procurement in Multi-agent Systems

Abstract

This paper addresses the problem of automated agent-based one-to-many negotiation for multi-issue service procurement and presents a robust negotiation mechanism to enhance the procurement process. Software agents represent service sellers and service buyers. Agents are assumed to have goals and constraints when buying and selling services. Automating the service procurement process can provide fast and efficient procurement results. The presented negotiation mechanism uses a concession tactic that facilitates service procurement from the best provider amongst multiple prospective providers. The strategy of the tactic is based on offering more concessions on the negotiation issues that are believed to be more preferred to the opponents. In other words, the tactic considers the preferences of the opponent agents on different negotiation issues (attributes) before selecting the amount of the concession on each issue. The negotiation mechanism is validated experimentally.

An Effective Negotiation Strategy for Quantitative and Qualitative Issues in Multi-Agent Systems

“…The proposed strategy is more effective compared to the baseline negotiation strategy. The work shown in [17,18] presents a preferential negotiating mechanism. During negotiations, the opponents' preferences concerning different matters are learned.…”

“…The proposed meta-negotiation strategy includes two mechanisms for generating offers; the preference-based mechanism is used for generating the quantitative issue offers and considers the opponent's preferences when formulating offers [17,18], while the the fuzzy similarity mechanism is used for generating the qualitative issues' offers [19].…”

“…Given the fact that a negotiating agent considers the preferences of its opponent, it is expected that the chances of reaching an agreement will improve. The negotiation mechanism of the preference-based approach is called the iterative offer generation concession (IOG-concession) which is a concession offer generation method where an agent needs to assign its current acceptable utility before starting generating a composite offer [17,18] (i.e., an offer contains values for more than one issue) for the next negotiation round where the weighted average utility of the generated composite offer should equal the pre-assigned utility. For the current offer, the minimum acceptable utility value should be smaller than the utility value of the previous composite offer.…”

“…It can be applied in different domains and addresses both quantitative and qualitative issues. In the case of quantitative offers, the preference-based negotiation strategy uses the fundamental assumption is that agent preferences differ over negotiation issues [17,18]. In contrast, the fuzzy similarity mechanism formulates the next offer for the qualitative issues [19].…”