Name
Abstract | ||
|---|---|---|
The present work initiates the study of the learnability of automatic indexable classes which are classes of regular languages
of a certain form. Angluin’s tell-tale condition characterizes when these classes are explanatorily learnable. Therefore,
the more interesting question is when learnability holds for learners with complexity bounds, formulated in the automata-theoretic
setting. The learners in question work iteratively, in some cases with an additional long-term memory, where the update function
of the learner mapping old hypothesis, old memory and current datum to new hypothesis and new memory is automatic. Furthermore,
the dependence of the learnability on the indexing is also investigated. This work brings together the fields of inductive
inference and automatic structures.
|
Year | DOI | Venue |
|---|---|---|
2012 | 10.1016/j.jcss.2011.12.011 | language and automata theory and applications |
Keywords | Field | DocType |
new hypothesis,automatic indexable class,automatic class,interesting question,additional long-term memory,question work iteratively,present work,old hypothesis,old memory,automatic structure,new memory,indexation,inductive inference,long term memory,regular language | Inductive reasoning,Geodetic datum,Computer science,Search engine indexing,Natural language processing,Artificial intelligence,Regular language,Learnability,Technical report | Journal |
Volume | Issue | ISSN |
78 | 6 | 0022-0000 |
ISBN | Citations | PageRank |
3-642-13088-7 | 9 | 0.54 |
References | Authors | |
28 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sanjay Jain | 1 | 1647 | 177.87 |
| Qinglong Luo | 2 | 14 | 0.95 |
| Frank Stephan | 3 | 215 | 39.36 |