This paper deals with two problems: (1) what makes languages learnable in the limit by natural strategies of varying hardness, and (2) what makes classes of languages the hardest ones to learn. To quantify hardness of learning, we use intrinsic complexity based on reductions between learning problem
The Intrinsic Complexity of Language Identification
โ Scribed by Sanjay Jain; Arun Sharma
- Book ID
- 102971674
- Publisher
- Elsevier Science
- Year
- 1996
- Tongue
- English
- Weight
- 522 KB
- Volume
- 52
- Category
- Article
- ISSN
- 0022-0000
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โฆ Synopsis
A new investigation of the complexity of language identification is undertaken using the notion of reduction from recursion theory and complexity theory. The approach, referred to as the intrinsic complexity of language identification, employs notions of weak'' and strong'' reduction between learnable classes of languages. The intrinsic complexity of several classes is considered and the results agree with the intuitive difficulty of learning these classes. Several complete classes are shown for both the reductions and it is also established that the weak and strong reductions are distinct. An interesting result is that the self-referential class of Wiehagen in which the minimal element of every language is a grammar for the language and the class of pattern languages introduced by Angluin are equivalent in the strong sense. This study has been influenced by a similar treatment of function identification by Freivalds, Kinber, and Smith.
๐ SIMILAR VOLUMES
A sequence over an alphabet Z is called disjunctirr if it contains all possible finite strings over .Z as its substrings. Disjunctive sequences have been recently studied in various contexts. They abound in both category and measure senses. In this paper we measure the complexity of a sequence x by