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A flexible plan step execution model for BDI agents

机译:BDI代理的灵活计划步骤执行模型

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摘要

For the past 20 years, BDI (Belief, Desire, Intention) frameworks such as PRS [1], dMARS [2] and JACK [3] have provided, together with Soar [4], the two environments of choice for the development of knowledge rich, industrial strength intelligent agent applications [5]. However, we have observed that while the BDI model of plan execution works well for the tactical reasoning component of such applications, operational reasoning often requires a richer execution model. In this paper, we present an alternative, but complementary model for plan step execution by BDI agents. In the BDI model, plan steps either succeed or fail; if a plan step fails, then the plan fails and reconsideration of the current goal may occur. We have found that this approach is problematic when used for applications where resource contention is a regular occurrence, such as in manufacturing execution [6]. In these situations, it is necessary to review progress after each step, regardless of the step outcome. Our alternative model for plan step execution allows for the explicit modelling of the plan step lifecycle and the utilisation of infrastructure to manage the progression of that lifecycle. The model is realised using the JACK? Intelligent Agents (JACK) product suite [3] and its feasibility is demonstrated through the development of an execution system for a robotic assembly cell.
机译:在过去的20年中,BDI(信念,愿望,意图)框架(例如PRS [1],dMARS [2]和JACK [3])与Soar [4]一起提供了两种开发环境的选择。知识丰富,具有工业实力的智能代理应用[5]。但是,我们已经观察到,尽管计划执行的BDI模型对于此类应用程序的战术推理组件非常有效,但是操作推理通常需要更丰富的执行模型。在本文中,我们为BDI代理执行计划步骤提供了一个替代性但互补的模型。在BDI模型中,计划步骤成功或失败;如果计划步骤失败,则计划失败,并且可能会重新考虑当前目标。我们发现,这种方法在经常发生资源争用的应用中(例如在制造执行中)使用时会出现问题[6]。在这些情况下,无论步骤结果如何,都必须在每个步骤之后检查进度。我们用于计划步骤执行的替代模型允许对计划步骤生命周期进行显式建模,并利用基础结构来管理该生命周期的进展。该模型是使用JACK实现的吗?智能代理(JACK)产品套件[3]及其可行性通过开发用于机器人装配单元的执行系统得到了证明。

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  • 来源
    《Multiagent and grid systems》 |2008年第4期|359-370|共12页
  • 作者单位

    Centre for Intelligent and Networked Systems, CQUniversity, Rockhampton, Queensland 4702, Australia;

    Centre for Intelligent and Networked Systems, CQUniversity, Rockhampton, Queensland 4702, Australia;

    Intendico Pty. Ltd. Suite 40, 85 Grattan St. Carlton Victoria 3053, Australia;

    KES Centre, School of Electrical and Information Engineering, University of South Australia, Levels Campus, South Australia 5095, Australia;

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