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高阶逻辑HOL4中有限状态离散马可夫链的形式化方法

Formal Reasoning About Finite-State Discrete-Time Markov Chains in HOL

  • 摘要: 离散马可夫链是具有单步记忆功能的时间和状态均离散的特殊马可夫随机过程。离散马可夫链广泛应用于物理学, 生物学, 社会学和很多不同工程学科领域, 特别是在工程系统的建模, 设计和检验过程中, 使用高阶逻辑马可夫链定理验证方法比使用数值测量, 数值仿真和物理模拟验证方法具有更完备, 更准确和扩展性更强的特征。因此近年来高阶逻辑概率模型和高阶逻辑马可夫链模型的形式化研究成为工程系统建模, 设计和验证方向的热点之一。本文在HOL4高阶逻辑平台上定义了有限状态齐次马可夫链模型, 并且用HOL4高阶逻辑验证它的一些重要性质如:联合分布概率密度函数、查普曼-科尔莫格洛夫等式及可反转性等。作为实用案例, 本文还应用该形式化的马可夫链及其性质分析了简化的二进制通信通道(Binary Communication Channel) 和自动邮件质量测量协议(AMQM protocol), 为形式化的马可夫链的应用提供了技术参考。

     

    Abstract: Markov chains are extensively used in modeling different aspects of engineering and scientific systems, such as performance of algorithms and reliability of systems. Different techniques have been developed for analyzing Markovian models, for example, Markov Chain Monte Carlo based simulation, Markov Analyzer, and more recently probabilistic model-checking. However, these techniques either do not guarantee accurate analysis or are not scalable. Higher-order-logic theorem proving is a formal method that has the ability to overcome the above mentioned limitations. However, it is not mature enough to handle all sorts of Markovian models. In this paper, we propose a formalization of Discrete-Time Markov Chain (DTMC) that facilitates formal reasoning about time-homogeneous finite-state discrete-time Markov chain. In particular, we provide a formal verification on some of its important properties, such as joint probabilities, Chapman-Kolmogorov equation, reversibility property, using higher-order logic. To demonstrate the usefulness of our work, we analyze two applications: a simplified binary communication channel and the Automatic Mail Quality Measurement protocol.

     

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