Actual real-world domains are characterised by uncertain situations in which acting and use of resources require embracing risk. Performing actions in such domains always entails costs of consuming some resource, such as time, money, or energy, where the knowledge about these costs can range from totally known to totally unknown and even unknowable probabilities of costs. Think of robotic domains, where actions and their costs are non-deterministic due to uncertain factors like obstacles. Choosing which action to perform considering its cost on the available resource requires taking a stance on risk. Thus, these domains call for not only planning under uncertainty but also planning while embracing risk. Taking Hierarchical Task Network (HTN) planning as a widely used planning technique in real-world applications, one can observe that existing approaches do not account for risk. That is, computing most probable or optimal plans using actions with single-valued costs is only enough to express risk neutrality. In this work, we postulate that HTN planning can become risk aware by considering expected utility theory, a representative concept of decision theory that enables choosing actions considering a probability distribution of their costs and a given risk attitude expressed using a utility function. In particular, we introduce a general framework for HTN planning that allows modelling risk and uncertainty using a probability distribution of action costs upon which we define risk-aware HTN planning as an approach that accounts for the different risk attitudes and allows computing plans that go beyond risk neutrality. In fact, we layout that computing risk-aware plans requires finding plans with the highest expected utility. Finally, we argue that it is possible for HTN planning agents to solve specialised risk-aware HTN planning problems by adapting some existing HTN planning approaches.
翻译:实际现实世界域的特征是不确定的情况,在这种情况下,资源的行动和使用需要承担风险。在这类领域采取行动往往需要消耗某些资源的成本,如时间、资金或能源等,在这些方面,有关成本的知识可能包括完全已知的、完全未知的、甚至无法理解的成本概率。想象机器人领域,由于各种障碍等不确定因素,在这些方面,行动及其成本不是决定性的。在考虑现有资源的成本时,选择哪些行动需要对风险采取风险立场。因此,这些领域不仅需要在不确定性下进行规划,而且还需要规划,同时要承担风险。在现实世界应用中,将等级化任务网络(HTN)规划作为广泛使用的规划技术,人们可以观察到现有方法并不考虑风险。这就是,利用单价值成本来计算最可能或最优的计划,这只能表达风险中性。在这项工作中,我们假设HTN规划规划可以通过考虑预期的实用性理论、具有代表性的TN决定理论,从而能够选择其成本的概率分布,在风险中,以特殊的风险态度来解释。在使用电算模型中,我们通过预测性计划进行一个总体的模型来定义一个成本分配。