IAMhaggler: A Negotiation Agent for Complex Environments
IAMhaggler: A Negotiation Agent for Complex Environments
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IAMhaggler：复杂环境的谈判代理
DOI：
10.1007/978-3-642-24696-8_10
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发表时间：
2012
期刊：
影响因子：
--
通讯作者：
N. Jennings
中科院分区：
文献类型：
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作者：
Colin R. Williams;V. Robu;E. Gerding;N. Jennings
我们描述了我们的代理IAMhaggler使用的策略，它在2010年自动谈判代理竞赛中获得了第三名。它使用让步策略来确定出价的效用水平。这种让步策略采用原则性的方法，考虑对手的出价。然后，它使用帕累托搜索算法与贝叶斯学习相结合，以生成具有其让步策略给定的特定效用的多问题报价。
We describe the strategy used by our agent, IAMhaggler, which finished in third place in the 2010 Automated Negotiating Agent Competition. It uses a concession strategy to determine the utility level at which to make offers. This concession strategy uses a principled approach which considers the offers made by the opponent. It then uses a Pareto-search algorithm combined with Bayesian learning in order to generate a multi-issue offer with a specific utility as given by its concession strategy.