Statistical Abduction with Tabulation
Statistical Abduction with Tabulation
复制标题
统计溯因与制表
DOI：
10.1007/3-540-45632-5_22
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发表时间：
2002
期刊：
影响因子：
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通讯作者：
Yoshitaka Kameya
中科院分区：
文献类型：
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作者：
Taisuke Sato;Yoshitaka Kameya
We proposestatistical abductionas a first-order logical framework for representing, inferring and learning probabilistic knowledge. It semantically integrates logical abduction with a parameterized distribution over abducibles. We show that statistical abduction combined with tabulated search provides an efficient algorithm for probability computation, a Viterbi-like algorithm for finding the most likely explanation, and an EM learning algorithm (the graphical EM algorithm) for learning parameters associated with the distribution which achieve the same computational complexity as those specialized algorithms for HMMs (hidden Markov models), PCFGs (probabilistic context-free grammars) and sc-BNs (singly connected Bayesian networks).
