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An Extended Alternating-Offers Bargaining Protocol for Automated Negotiation in Multi-agent Systems

机译:用于多智能体系统中自动协商的扩展的交替要价谈判协议

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Depending on the protocol type, a negotiation can be categorized as an auction, a contract-net protocol, or a voting or bargaining scheme. While most research focuses on auctions because the strategy is simple, bargaining is still an important way of negotiation. This is because 1. auctions only allow negotiation for price, not other attributes (delivery time, payment method, delivery method, etc.); 2. auctions usually are scheduled in advance and with time restrictions, but some buyers/sellers may not want to wait until an auction opens or finalizes; 3. in some cases, many social factors are important, e.g., trusteeships, friendships, etc., which auctions cannot easily accommodate; 4. most auctions extract the surplus for the benefit of the auctioneer, especially if there is a significant number of bidders. Generally, the bargaining model in Multi-Agent Systems (MAS) adopts the classical alternating-offers model. Currently, there are many variants of this model, such as a model with time deadline (Krauss, Wilkenfeld and Zlotkin 1995; Sandholm and Vulkan 1999), with various information levels (complete/incomplete, symmetric/ asymmetric), with risk of breakdown (one party walks out before negotiation ends), etc. Most of the theoretical foundations have been studied by game theorists (Nash 1950; Rubinstein 1982). However, there is one important limitation of the game-theoretic approach, i.e., searching the solution in exhaustive fashion. Considering the limitation of computational power, many heuristic techniques are adopted to develop new models, namely heuristic-based negotiation models, characterized by learning mechanisms such as Bayesian learning (Zeng and Sycara 1998), influence diagrams (Mudgal and Vassileva 2000), evolutionary algorithm (van Bragt, Gerding and LaPoutre 2000). Using these models, the negotiators can make decisions faster to find a good solution, although not necessarily the best one. In addition, some researchers have proposed an argumentation-based model that focuses on natural-language-like negotiation (Hulstijn, Dastani and van der Torre 2001; Jennings et al. 2001; Sycara 1989). The main idea of this work is to provide more flexibility in the negotiation process, such as to allow a negotiator to persuade their opponents to change their perceptions.
机译:根据协议类型的不同,可以将协商分为拍卖,合同网络协议或投票或讨价还价方案。尽管大多数研究都因为策略简单而将重点放在拍卖上,但讨价还价仍然是谈判的重要方式。这是因为1.拍卖仅允许协商价格,而不能协商其他属性(交付时间,付款方式,交付方式等); 2.拍卖通常是预先安排的,并且有时间限制,但是某些买家/卖家可能不想等到拍卖开始或完成时; 3.在某些情况下,许多社会因素很重要,例如,托管,友谊等,拍卖无法轻易地满足这些因素; 4.大多数拍卖会为拍卖人的利益提取盈余,特别是在有大量投标人的情况下。通常,多代理系统(MAS)中的讨价还价模型采用经典的交替报价模型。当前,该模型有许多变体,例如具有时间期限的模型(Krauss,Wilkenfeld和Zlotkin 1995; Sandholm和Vulkan 1999),具有各种信息级别(完全/不完全,对称/非对称),存在崩溃的风险(博弈论家已经研究了大多数理论基础(纳什,1950;鲁宾斯坦,1982)。但是,博弈论方法有一个重要的局限性,即以穷举的方式寻找解决方案。考虑到计算能力的限制,许多启发式技术被用来开发新的模型,即基于启发式的协商模型,其特征在于学习机制,如贝叶斯学习(Zeng和Sycara 1998),影响图(Mudgal和Vassileva 2000),进化算法。 (van Bragt,Gerding and LaPoutre 2000)。使用这些模型,谈判者可以更快地做出决策以找到一个好的解决方案,尽管不一定是最好的解决方案。此外,一些研究人员提出了一种基于论证的模型,该模型侧重于类似自然语言的谈判(Hulstijn,Dastani和van der Torre 2001; Jennings等2001; Sycara 1989)。这项工作的主要思想是在谈判过程中提供更大的灵活性,例如允许谈判者说服对手改变看法。

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