Minimization of Limit-Average Automata
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence. Main Track. Pages 2819-2825.
https://doi.org/10.24963/ijcai.2021/388
Keywords
- Agent-based and Multi-agent Systems: Formal Verification, Validation and Synthesis
- Machine Learning: Active Learning
- Multidisciplinary Topics and Applications: Validation and Verification
Abstract
LimAvg-automata are weighted automata over infinite words that aggregate weights along runs with the limit-average value function.
In this paper, we study the minimization problem for (deterministic) LimAvg-automata.
Our main contribution is an equivalence relation on words characterizing LimAvg-automata, i.e.,
the equivalence classes of this relation correspond to states of an equivalent LimAvg-automaton.
In contrast to relations characterizing DFA, our relation depends not only on the function defined by the target automaton, but also on its structure.
We show two applications of this relation.
First, we present a minimization algorithm for LimAvg-automata, which returns a minimal LimAvg-automaton among those equivalent and structurally similar to the input one.
Second, we present an extension of Angluin's L^*-algorithm with syntactic queries, which learns in polynomial time a LimAvg-automaton equivalent to the target one.
@inproceedings{ijcai2021p388,
title = {Minimization of Limit-Average Automata},
author = {Michaliszyn, Jakub and Otop, Jan},
booktitle = {Proceedings of the Thirtieth International Joint Conference on
Artificial Intelligence, {IJCAI-21}},
publisher = {International Joint Conferences on Artificial Intelligence Organization},
editor = {Prof. Zhi-Hua Zhou},
pages = {2819--2825},
year = {2021},
month = {8},
note = {Main Track},
doi = {10.24963/ijcai.2021/388},
url = {https://doi.org/10.24963/ijcai.2021/388},
}
TY - CPAPER TI - Minimization of Limit-Average Automata AU - Michaliszyn, Jakub AU - Otop, Jan T2 - Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, IJCAI-21 PB - International Joint Conferences on Artificial Intelligence Organization PY - 2021 SP - 2819 EP - 2825 DO - 10.24963/ijcai.2021/388 UR - https://doi.org/10.24963/ijcai.2021/388 ER -Copied
Machine-readable versions of this paper, for tools and AI agents: