Deciding Roles for Efficient Team Formation by Parameter Learning
Deciding Roles for Efficient Team Formation by Parameter Learning
复制标题
通过参数学习确定角色以实现高效团队组建
DOI：
10.1007/978-3-642-30947-2_59
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发表时间：
2012
期刊：
影响因子：
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通讯作者：
Dai Hamada and Toshiharu Sugawara
中科院分区：
文献类型：
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作者：
Miki Hirabayashi;Ibuki Kawamata;Masami Hagiya;Hiroaki Kojima;andKazuhiro Oiwa;Dai Hamada and Toshiharu Sugawara
我们提出了一种学习方法，用于在面向任务的领域中通过自利代理有效地组建团队。计算机网络上的服务请求最近迅速增加。为了提高此类系统的性能，有效团队组建来完成任务的问题引起了我们的兴趣。该方法的主要特点是从两侧的观点学习，即主动组建团队的团队领导者或在被邀请的团队之一工作的团队成员。为此，我们向智能体引入三个参数，以便智能体可以选择自己的角色是领导者还是成员，然后智能体可以预测应该选择哪些其他智能体作为团队成员以及应该加入哪个团队。我们的实验表明，与传统方法相比，成功生成的团队执行的任务数量增加了约 17%。
We propose a learning method for efficient team formation by self-interested agents in task oriented domains. Service requests on computer networks have recently been rapidly increasing. To improve the performance of such systems, issues with effective team formation to do tasks has attracted our interest. The main feature of the proposed method is learning from two-sided viewpoints, i.e., team leaders who have the initiative to form teams or team members who work in one of the teams that are solicited. For this purpose, we introduce three parameters to agents so that they can select their roles of being a leader or a member, then an agent can anticipate which other agents should be selected as team members and which team it should join. Our experiments demonstrated that the numbers of tasks executed by successfully generated teams increased by approximately 17% compared with a conventional method.