Hierarchical Multi-Agent Plans Using Model-Based Petri Net

Said Brahimi, R. Maamri, Z. Sahnoun
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引用次数: 8

Abstract

Agents evolving in complex and dynamic multi-agent systems need to plan their tasks and to adapt their behavior in order to react to unpredictable events. Therefore they must have plans that remain subject to continual updating, even during its execution. Although this property is important in dynamic environments, it is difficult to have a trade-off between the convergence towards the goal to be reached and the reaction to unanticipated events. To cope with this issue, it is needed to have a model allowing to represent plans less sensitive to execution contexts, and to support flexible execution. This paper aims to provide an adequate plan representation, by taking advantage of hierarchical plans and extensions to Petri net. The authors extend the Petri net to take into account the different abstraction levels of plans and the resources required by tasks. To cope with the interdependence of tasks, the authors include in the model, a synchronization mechanism between concurrent transitions. The proposed model can be used to reason on abstract levels of plans and to analyze, in a dynamic way, situations in which the execution of the plan can be performed in any ways, in some ways, or cannot be performed. Hierarchical Multi-Agent Plans Using Model-Based Petri Net
基于模型Petri网的分层多智能体规划
在复杂、动态的多智能体系统中,智能体需要对自己的任务进行规划,调整自己的行为,以便对不可预测的事件做出反应。因此,他们必须有持续更新的计划,即使在执行期间也是如此。尽管这一特性在动态环境中很重要,但很难在趋同目标和对意外事件的反应之间做出权衡。为了解决这个问题,需要有一个模型来表示对执行上下文不那么敏感的计划,并支持灵活的执行。本文的目的是利用分层规划和对Petri网的扩展,提供一个充分的规划表示。作者扩展了Petri网,以考虑到不同的计划抽象级别和任务所需的资源。为了处理任务之间的相互依赖,作者在模型中包含了并发转换之间的同步机制。所建议的模型可用于在计划的抽象层次上进行推理,并以动态的方式分析计划的执行可以以任何方式执行、以某些方式执行或不能执行的情况。基于模型Petri网的分层多智能体规划
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