Understanding intelligence
Introduction to Multiagent Systems
Introduction to Multiagent Systems
Scientific approaches and techniques for negotiation. A game theoretic and artificial intelligence perspective
A Negotiation Meta Strategy Combining Trade-off and Concession Moves
Autonomous Agents and Multi-Agent Systems
Benefits of learning in negotiation
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
Bilateral negotiation decisions with uncertain dynamic outside options
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
| Hi-index | 0.00 |
Finding the adequate (win-win solutions for both parties) negotiation strategy with incomplete information for autonomous agents, even in one-toone negotiation, is a complex problem. Elsewhere, negotiation behaviors, in which the characters such as conciliatory or aggressive define a 'psychological' aspect of the negotiator personality, play an important role. The aim of this paper to develop a fuzzy cognitive and social negotiation strategy for autonomous agents with incomplete information, where the characters conciliatory, neutral, or aggressive, are suggested to be integrated in negotiation behaviors (inspired from research works aiming to analyze human behavior and those on social negotiation psychology). For this purpose, first, one-to-one bargaining process, in which a buyer agent and a seller agent negotiate over single issue (price), is developed for a time-dependent strategy (based on time-dependent behaviors of Faratin et al .) and for a fuzzy cognitive and social strategy. Second, experimental environments and measures, allowing a set of experiments, carried out for different negotiation deadlines of buyer and seller agents, are detailed. Third, experimental results for both time-dependent and fuzzy cognitive and social strategies are presented, analyzed, and compared for different deadlines of agents. The suggested fuzzy cognitive and social strategy allows agents to improve the negotiation process, with regard to the time-dependent one, in terms of agent utilities, round number to reach an agreement, and percentage of agreements.