Fostering resilient execution of multi-agent plans through self-organisation

Giorgio Audrito, Roberto Casadei, G. Torta
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引用次数: 7

Abstract

Traditional multi-agent planning addresses the coordination of multiple agents towards common goals, by producing an integrated plan of actions for each of those agents. For systems made of large numbers of cooperating agents, however, the execution and monitoring of a plan should enhance its high-level steps, possibly involving entire sub-teams, with a flexible and adaptable lower-level behaviour of the individual agents. In order to achieve such a goal, we need to integrate the behaviour dictated by a multi-agent plan with self-organizing, swarm-based approaches, capable of automatically adapting their behaviour based on the contingent situation, departing from the predetermined plan whenever needed. Moreover, in order to deal with multiple domains and unpredictable situations, the system should, as far as possible, exhibit such capabilities without hard-coding the agents behaviour and interactions. In this paper, we investigate the relationship between multi-agent planning and self-organisation through the combination of two representative approaches both enjoying declarativity. We consider a functional approach to self-organising systems development, called Aggregate Programming (AP), and propose to exploit collective adaptive behaviour to carry out plan revisions. We describe preliminary results in this direction on a case study of execution monitoring and repair of a Multi-Agent PDDL plan.
通过自组织促进多代理计划的弹性执行
传统的多智能体规划通过为每个智能体生成一个综合的行动计划来解决多个智能体朝着共同目标的协调问题。然而,对于由大量合作代理人组成的系统,计划的执行和监测应加强其高级别步骤,可能涉及整个分小组,而个别代理人则有灵活和适应性强的较低级别行为。为了实现这一目标,我们需要将多代理计划所决定的行为与自组织、基于群体的方法结合起来,这些方法能够根据偶然情况自动调整它们的行为,在需要时离开预定的计划。此外,为了处理多个领域和不可预测的情况,系统应该尽可能在不硬编码代理行为和交互的情况下表现出这样的能力。本文通过结合两种具有代表性的具有声明性的方法来研究多智能体规划和自组织之间的关系。我们考虑了一种自组织系统开发的功能方法,称为聚合规划(AP),并建议利用集体适应行为来执行计划修订。我们在多代理PDDL计划的执行监视和修复的案例研究中描述了这方面的初步结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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