Title
MAT learners for tree series: an abstract data type and two realizations
Abstract
We propose abstract observation tables, an abstract data type for learning deterministic weighted tree automata in Angluin’s minimal adequate teacher (MAT) model, and show that every correct implementation of abstract observation tables yields a correct MAT learner. Besides the “classical” observation table, we show that abstract observation tables can also be implemented by observation trees. The advantage of the latter is that they often require fewer queries to the teacher.
Year
DOI
Venue
2011
10.1007/s00236-011-0135-x
Acta Inf.
Keywords
Field
DocType
observation table,abstract observation tables yield,fewer query,minimal adequate teacher,correct mat learner,tree series,abstract data type,deterministic weighted tree automaton,correct implementation,observation tree,abstract observation table,computer science
Abstract data type,Deterministic automaton,Computer science,Automaton,Theoretical computer science,Tree automaton
Journal
Volume
Issue
ISSN
48
3
1432-0525
Citations 
PageRank 
References 
3
0.40
15
Authors
3
Name
Order
Citations
PageRank
Frank Drewes1266.10
Johanna Högberg2946.72
Andreas Maletti336538.59