Abstract The trisecting-acting-outcome (TAO) model of three-way decisions comprises three components, i.e., constructing a trisection, strategies for action, and measuring the outcome. Existing research seldom involves the third component, i.e., measuring the effectiveness of the outcome. A previous study provides a strategy select method by analyzing benefits or costs in the movement-based three-way decision. However, we often choose a strategy depend on the probability or distribution of three regions instead of the benefits or costs. In this paper, we propose a probabilistic movement model of three-way decision and give a strategy selection mechanism based on information entropy. Conditional entropy and cross entropy are used to select strategies by measuring these probabilities according to the user's preferences and structural features of the three partitions. It selects the action or strategy which has the maximum probability of desirable movements based on the minimization of the conditional entropy. It also selects the action or strategy which has the least difference between actual probabilistic distributions and expected probabilistic distribution based on the minimization of the cross entropy. We give two examples to illustrate the practicality and effectiveness of the strategy selection method in the probabilistic movement model of three-way decision.

中文翻译：

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基于运动的三向决策中熵测度下的策略选择

摘要 三向决策的三等分-行动-结果（TAO）模型包括三个组成部分，即构建三等分、行动策略和衡量结果。现有研究很少涉及第三个组成部分，即衡量结果的有效性。先前的研究通过分析基于运动的三向决策中的收益或成本提供了一种策略选择方法。然而，我们通常选择的策略取决于三个区域的概率或分布，而不是收益或成本。在本文中，我们提出了一种三向决策的概率运动模型，并给出了一种基于信息熵的策略选择机制。条件熵和交叉熵用于通过根据用户的测量这些概率来选择策略。三个分区的偏好和结构特征。它基于条件熵的最小化来选择具有最大期望运动概率的动作或策略。它还基于交叉熵的最小化选择实际概率分布与预期概率分布之间差异最小的动作或策略。我们通过两个例子来说明策略选择方法在三向决策概率运动模型中的实用性和有效性。它还基于交叉熵的最小化选择实际概率分布与预期概率分布之间差异最小的动作或策略。我们通过两个例子来说明策略选择方法在三向决策概率运动模型中的实用性和有效性。它还基于交叉熵的最小化选择实际概率分布与预期概率分布之间差异最小的动作或策略。我们通过两个例子来说明策略选择方法在三向决策概率运动模型中的实用性和有效性。