关于感测动作和部分状态的回归
Regression with respect to sensing actions and partial states
摘要：
在本文中，我们提出了一个基于状态的回归函数规划域的代理不具有完整的信息，可能有传感器的行动。我们考虑二进制域，并采用0近似[Son & Baral 2001]来定义回归函数。在二进制域中，使用0近似意味着使用3值状态。虽然规划使用这种方法是不完整的完整的语义，我们采用它有一个较低的复杂性。我们证明了我们的回归公式的稳健性和完整性相对于进展的定义。更具体地说，我们证明了（i）通过回归获得的规划问题的计划确实是该规划问题的级数解，以及（ii）对于通过级数找到的每个计划，使用回归获得该计划或等效计划。然后，我们开发了一个条件规划器，利用我们的回归函数。我们证明了我们的规划算法的合理性和完整性，并在文献中几个著名的规划问题的实验结果。
英文摘要：
In this paper, we present a state-based regression function for planning domains where an agent does not have complete information and may have sensing actions. We consider binary domains and employ the 0-approximation [Son & Baral 2001] to define the regression function. In binary domains, the use of 0-approximation means using 3-valued states. Although planning using this approach is incomplete with respect to the full semantics, we adopt it to have a lower complexity. We prove the soundness and completeness of our regression formulation with respect to the definition of progression. More specifically, we show that (i) a plan obtained through regression for a planning problem is indeed a progression solution of that planning problem, and that (ii) for each plan found through progression, using regression one obtains that plan or an equivalent one. We then develop a conditional planner that utilizes our regression function. We prove the soundness and completeness of our planning algorithm and present experimental results with respect to several well known planning problems in the literature.
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