Heerdt, GV;
Kappé, T;
Rot, J;
Silva, A;
(2021)
Learning Pomset Automata.
In: Kiefer, S and Tasson, C, (eds.)
Foundations of Software Science and Computation Structures. FOSSACS 2021.
(pp. pp. 510-530).
Springer: Cham, Switzerland.
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Abstract
We extend the L⋆ algorithm to learn bimonoids recognising pomset languages. We then identify a class of pomset automata that accepts precisely the class of pomset languages recognised by bimonoids and show how to convert between bimonoids and automata.
| Type: | Proceedings paper |
|---|---|
| Title: | Learning Pomset Automata. |
| Event: | FOSSACS 2021: Foundations of Software Science and Computation Structures |
| ISBN-13: | 978-3-030-71994-4 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1007/978-3-030-71995-1_26 |
| Publisher version: | https://doi.org/10.1007/978-3-030-71995-1_26 |
| Language: | English |
| Additional information: | © The Author(s) 2021 Open Access This chapter is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made. The images or other third party material in this chapter are included in the chapter's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the chapter's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10125752 |
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