Reasoning about actions in a probabilistic setting
Reasoning about actions in a probabilistic setting
复制标题
在概率环境中推理行动
DOI：
10.5555/777092.777171
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发表时间：
2002
期刊：
影响因子：
--
通讯作者：
Le
中科院分区：
文献类型：
--
作者：
Chitta Baral;Tran Hoai Nam;Le
在本文中，我们提出了一种在概率环境中推理行为的语言，并将我们的工作与 Pearl 的早期工作进行比较。我们语言的主要特点是使用静态和动态因果律，以及在合并概率时使用未知（或背景）变量（其值由模型之外的因素决定）。我们使用两种未知变量：惯性和非惯性。惯性未知变量有助于同化观察结果以及对反事实和因果关系进行建模；而非惯性未知变量有助于表征不受观察影响的随机行为，例如抛硬币的结果。最后，我们将了解如何将概率融入叙事推理中。
In this paper we present a language to reason about actions in a probabilistic setting and compare our work with earlier work by Pearl.The main feature of our language is its use of static and dynamic causal laws, and use of unknown (or background) variables - whose values are determined by factors beyond our model - in incorporating probabilities. We use two kind of unknown variables: inertial and non-inertial. Inertial unknown variables are helpful in assimilating observations and modeling counterfactuals and causality; while non-inertial unknown variables help characterize stochastic behavior, such as the outcome of tossing a coin, that are not impacted by observations. Finally, we give a glimpse of incorporating probabilities into reasoning with narratives.