Name
Abstract | ||
|---|---|---|
The general goal of query-based learning algorithms for finite-state machines is to identify a machine, usually of minimum size, that agrees with an a priori fixed (class of) machines. For this, queries on how the underlying system behaves may be issued. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1007/11872436_30 | ICGI |
Keywords | Field | DocType |
general goal,underlying system,minimum size,finite-state machine,query-based learning algorithm,inexperienced teacher,state machine,finite state machine | Online machine learning,Pointer machine,Active learning (machine learning),Computer science,A priori and a posteriori,Finite-state machine,Artificial intelligence,Virtual finite-state machine,Computational learning theory,Machine learning | Conference |
Volume | ISSN | ISBN |
4201 | 0302-9743 | 3-540-45264-8 |
Citations | PageRank | References |
3 | 0.39 | 4 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Olga Grinchtein | 1 | 115 | 7.91 |
| Martin Leucker | 2 | 1639 | 112.68 |