在多代理协作中使用基于任务的对话

U. Wajid, N. Mehandjiev
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引用次数: 0

摘要

软件代理的新协作模型可以比预定义的协议更灵活。为此,我们利用对话结构理论(DST)对人类互动的分析,设计了一种基于任务型对话(tbd)的智能体交互方法。本文描述了tbd的以下基本结构:表示系统中代理意图的共享任务层次结构,使代理能够构建有意义的消息序列的对话模型,以及对话状态存储库。该方法将这些基本成分集成到软件代理中,并允许代理实现不同的策略以实现其任务。tbd的一个示例显示了当对话由共享任务规范驱动,而不是由消息类型或执行序列驱动时,消息序列如何发展,超出了单个协议的能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Using Task-Based Dialogues for Multi-agent Collaborations
New collaboration models for software agents can be made more flexible than pre-defined protocols. In pursuit of this, we have used the analysis of human interactions from Dialogue Structure Theory (DST) and devised an agent interaction approach which is based on Task-Based Dialogues (TBDs). This paper describes the following basic constructs of TBDs: a shared task hierarchy to represent agent intentions in the system, a dialogue model that enables agents to construct a meaningful sequence of messages, and a repository of dialogue states. The approach integrates these fundamental ingredients in software agents, and allows agents to implement different strategies in order to achieve their tasks. An example of TBDs shows how a sequence of messages can evolve that is beyond the capability of a single protocol, when the dialogues are driven by shared task specifications and not by a sequence of message types or performatives.
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