Learning Probabilistic Automata and Markov Chains via Queries
Abstract
We investigate the problem of learning probabilistic automata and Markov chains via queries in the teacher-student learning model. Probabilistic automata and Markov chains are probabilistic extensions of finite state automata and have similar structures. We discuss some natural oracles associated with probabilistic automata and Markov chains. We present polynomial-time algorithms for learning probabilistic automata and Markov Chains using these oracles.
Cite
Text
Tzeng. "Learning Probabilistic Automata and Markov Chains via Queries." Machine Learning, 1992. doi:10.1007/BF00992862Markdown
[Tzeng. "Learning Probabilistic Automata and Markov Chains via Queries." Machine Learning, 1992.](https://mlanthology.org/mlj/1992/tzeng1992mlj-learning/) doi:10.1007/BF00992862BibTeX
@article{tzeng1992mlj-learning,
title = {{Learning Probabilistic Automata and Markov Chains via Queries}},
author = {Tzeng, Wen-Guey},
journal = {Machine Learning},
year = {1992},
pages = {151-166},
doi = {10.1007/BF00992862},
volume = {8},
url = {https://mlanthology.org/mlj/1992/tzeng1992mlj-learning/}
}