Tree-Based Adaptive Model Learning
arXiv:2209.00122 · doi:10.1007/978-3-031-15629-8_10
Abstract
We extend the Kearns-Vazirani learning algorithm to be able to handle systems that change over time. We present a new learning algorithm that can reuse and update previously learned behavior, implement it in the LearnLib library, and evaluate it on large examples, to which we make small adjustments between two runs of the algorithm. In these experiments our algorithm significantly outperforms both the classic Kearns-Vazirani learning algorithm and the current state-of-the-art adaptive algorithm.
10 pages, 3 figures, A Journey from Process Algebra via Timed Automata to Model Learning. Ferreira, T., van Heerdt, G., Silva, A. (2022). Tree-Based Adaptive Model Learning. In: Jansen, N., Stoelinga, M., van den Bos, P. (eds) A Journey from Process Algebra via Timed Automata to Model Learning; Full implementation and experiment results available at https://github.com/UCL-PPLV/learnlib