Language Evolution and Computation Bibliography

Language learnability has been investigated. This refers to the following situation: A class of possible languages is specified, together with a method of presenting information to the learner about an unknown language, which is to be chosen from the class. The question is now asked, ``Is the information sufficient to determine which of the possible languages is the unknown language?'' Many definitions of learnability are possible, but only the following is considered here: Time is quantized and has a finite starting time. At each time the learner receives a unit of information and is to make a guess as to the identity of the unknown language on the basis of the information received so far. This process continues forever. The class of languages will be considered learnable with respect to the specified method of information presentation if there is an algorithm that the learner can use to make his guesses, the algorithm having the following property: Given any language of the class, there is some finite time after which the guesses will all be the same and they will be correct.

In this preliminary investigation, a language is taken to be a set of strings on some finite alphabet. The alphabet, is the same for all languages of the class. Several variations of each of the following two basic methods of information presentation are investigated: A text for a language generates the strings of the language in any order such that every string of the language occurs at. least once. An informant for a language tells whether a string is in the language, and chooses the strings in some order such that every string occurs at least once. It was found that the class of context-sensitive languages is learnable from an informant, but that, not even the class of regular languages is learnable from a text.