Quantitative modelling and analysis of BDI agents
Quantitative modelling and analysis of BDI agents
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DOI：
10.1007/s10270-023-01121-5
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发表时间：
2023-08-28
影响因子：
2
通讯作者：
Xu，Mengwei
中科院分区：
文献类型：
--
作者：
Archibald，Blair;Calder，Muffy;Xu，Mengwei
信念-愿望-意图（BDI）Agent是一种流行的Agent体系结构。我们扩展的概念代理符号（可以）-BDI编程语言与先进的功能，如故障恢复和声明性的目标，包括概率的行动结果，例如，以反映失败的执行器，和概率的政策，例如概率计划和意图选择。扩展编码在米尔纳的双图。通过应用我们的BigraphER工具和PRISM模型检查器，可以研究和比较不同概率结果和计划/事件/意图选择策略下的成功概率（意图完成）。我们提出了一个智能制造用例。一个重要的结果是，计划选择与意图选择相比，效果有限。我们还看到，行动失败的影响可能是边际的，即使失败的概率很大，由于代理人作出更明智的选择。
Belief–desire–intention (BDI) agents are a popular agent architecture. We extend conceptual agent notation (Can)—a BDI programming language with advanced features such as failure recovery and declarative goals—to include probabilistic action outcomes, e.g. to reflect failed actuators, and probabilistic policies, e.g. for probabilistic plan and intention selection. The extension is encoded in Milner’s bigraphs. Through application of our BigraphER tool and the PRISM model checker, theprobabilityof success (intention completion) under different probabilistic outcomes and plan/event/intention selection strategies can be investigated and compared. We present a smart manufacturing use case. A significant result is that plan selection has limited effect compared with intention selection. We also see that the impact of action failures can be marginal—even when failure probabilities are large—due to the agent making smarter choices.