将规划中的投影抽象与马尔可夫决策过程框架统一，揭示两者异同。
Projection Abstractions in Planning Under the Lenses of Abstractions for MDPs
- 从规划视角出发，用马尔可夫决策过程的抽象框架重构投影抽象
- 证明同一抽象在两类方法中可等价构建，但计算与表示特性不同
- 为规划与强化学习交叉研究提供新方向，适合关注抽象建模的研究者
抽象概念在人工智能规划与折扣马尔可夫决策过程（MDPs）中被独立发展。尽管二者存在诸多共性，其构建方式和使用范式却不同。至今尚无工作系统性地关联并统一这两个领域关于抽象的研究，揭示其中假设差异及其影响。本文通过折扣MDP的视角审视规划中的投影抽象：从经典或概率规划技术构建的投影抽象出发，展示其如何在折扣MDP的抽象框架下实现。过程中对比了两者的计算与表示优劣，指出了对两个领域均有意义的新研究方向。
原文摘要 · Abstract (English)
The concept of abstraction has been independently developed both in the context of AI Planning and discounted Markov Decision Processes (MDPs). However, the way abstractions are built and used in the context of Planning and MDPs is different even though lots of commonalities can be highlighted. To this day there is no work trying to relate and unify the two fields on the matter of abstractions unraveling all the different assumptions and their effect on the way they can be used. Therefore, in this paper we aim to do so by looking at projection abstractions in Planning through the lenses of discounted MDPs. Starting from a projection abstraction built according to Classical or Probabilistic Planning techniques, we will show how the same abstraction can be obtained under the abstraction frameworks available for discounted MDPs. Along the way, we will focus on computational as well as representational advantages and disadvantages of both worlds pointing out new research directions that are of interest for both fields.
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