The definition and representation of planning problems is at the heart of AI planning research. A key part is the representation of action models. Decades of advances improving declarative action model representations resulted in numerous theoretical advances, and capable, working, domain-independent planners. However, despite the maturity of the field, AI planning technology is still rarely used outside the research community, suggesting that current representations fail to capture real-world requirements, such as utilizing complex mathematical functions and models learned from data. We argue that this is because the modeling process is assumed to have taken place and completed prior to the planning process, i.e., offline modeling for offline planning. There are several challenges inherent to this approach, including: limited expressiveness of declarative modeling languages; early commitment to modeling choices and computation, that preclude using the most appropriate resolution for each action model -- which can only be known during planning; and difficulty in reliably using non-declarative, learned, models. We therefore suggest to change the AI planning process, such that is carries out online modeling in offline planning, i.e., the use of action models that are computed or even generated as part of the planning process, as they are accessed. This generalizes the existing approach (offline modeling). The proposed definition admits novel planning processes, and we suggest one concrete implementation, demonstrating the approach. We sketch initial results that were obtained as part of a first attempt to follow this approach by planning with action cost estimators. We conclude by discussing open challenges.
翻译:规划问题的定义和表述是AI规划研究的核心。一个关键部分是行动模式的代表性。十年来改进宣示行动模式的先进表现导致许多理论进步,以及能够发挥作用的、独立的领域规划者。然而,尽管实地已经成熟,但AI规划技术仍然很少在研究界之外使用,这表明目前的表述未能反映现实世界的要求,例如利用复杂的数学功能和从数据中学习的模式。我们争辩说,这是因为模型进程假定是在规划过程之前就已经建立和完成的,即离线规划的离线模型。这一方法存在若干固有的挑战,包括:宣示性示范语言的清晰度有限;对建模和计算的初步承诺,排除了对每一种行动模式使用最适当的决议 -- -- 这只能在规划过程中才能知道;以及难以可靠地使用非宣示性的、学到的模型。我们因此建议改变AI规划进程,在离线规划过程中采用公开的建模方法,即离线下规划的离线建模模式,即使用初步的模型,作为总的规划过程的一部分,我们通过现有的规划过程来完成。我们通过初步的讨论,通过目前的规划过程来得出一个初步的模型,我们通过现有的规划过程来得出了一个新的规划过程的结论。