An operational semantics for the goal life-cycle in BDI agents
An operational semantics for the goal life-cycle in BDI agents
复制标题
BDI 代理中目标生命周期的操作语义
DOI：
10.1007/s10458-013-9238-9
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发表时间：
2013
影响因子：
1.9
通讯作者：
N. Yorke
中科院分区：
文献类型：
--
作者：
James Harland;David N. Morley;John Thangarajah;N. Yorke
智能代理的一个基本特征是他们能够深思熟虑自己的目标。在一个可能以不可预测的方式变化的环境中操作，代理需要定期评估其当前的目标集是否是要追求的最合适的集。因此，目标的管理是代理体系结构的一个关键方面。聚焦于BDI代理，我们考虑了文献中研究的各种类型的目标，包括实现目标和维护目标。我们开发了对目标状态的详细描述(例如目标是否已被挂起)，以及可应用于目标的一套全面的操作(包括删除、中止、挂起和继续)。我们用一种抽象的代理语言(CAN)提供了对应于这一详细描述的操作语义，并在一个详细的现实场景中进行了演示。我们的通用目标状态和转换框架的三个关键贡献是(1)包含完成目标和丰富的监控目标，(2)为所有常见目标类型提供第一个中止和挂起规范，以及(3)考虑计划执行以及次目标的动态。我们的语义澄清了代理如何根据它选择做出的决策来管理其目标，并进一步为代理行为的正确性验证提供了基础。
A fundamental feature of intelligent agents is their ability to deliberate over their goals. Operating in an environment that may change in unpredictable ways, an agent needs to regularly evaluate whether its current set of goals is the most appropriate set to pursue. The management of goals is thus a key aspect of an agent’s architecture. Focusing on BDI agents, we consider the various types of goals studied in the literature, including both achievement and maintenance goals. We develop a detailed description of goal states (such as whether goals have been suspended or not), and a comprehensive suite of operations that may be applied to goals (including dropping, aborting, suspending and resuming them). We provide an operational semantics corresponding to this detailed description in an abstract agent language (CAN), and demonstrate on a detailed real-life scenario. The three key contributions of our generic framework for goal states and transitions are (1) to encompass both goals of accomplishment and rich goals of monitoring, (2) to provide the first specification of abort and suspend for all the common goal types, and (3) to account for plan execution as well as the dynamics of subgoaling. Our semantics clarifies how an agent can manage its goals, based on the decisions that it chooses to make, and further provides a foundation for correctness verification of agent behaviour.