Classification of automata
All automata referred to from this point on may be understood to be essentially Turing machines classified in terms of the number, length, and movement of tapes and of the reading and writing operations used. The term discrete state automaton is sometimes used to emphasize the discrete nature of the internal states. The principal classes are transducers and acceptors. In automata theory, a transducer is an automaton with input and output; any Turing machine for computing a partial recursive function, as previously described, can stand as an example. An acceptor is an automaton without output that, in a special sense, recognizes or accepts words on the machine alphabet. The input of an acceptor is written on tape in the usual way, but the tape is blank at the end of the computation, and acceptance of the input word is represented by a special state called a final state. Thus, a word x, or sequence of symbols from an alphabet denoted by the letter S, is said to be accepted by an acceptor A if A computes, beginning in an initial state q0 with x on tape, and halts in a final state with tape being entirely blank. A subset designated U of the set of words S* on an alphabet S is called an accepted set if there is an automaton A that accepts any word x ∊ U.
Acceptors
An elementary result of automata theory is that every recursively enumerable set, or range of a partial recursive function, is an accepted set. In general the acceptors are two-way unbounded tape automata.
A useful classification of acceptors has been introduced in conjunction with a theory of generative grammars developed in the United States by a linguist, Noam Chomsky. A generative grammar is a system of analysis usually identified with linguistics. By its means a language can be viewed as a set of rules, finite in number, that can produce sentences. The use of a generative grammar, in the context of either linguistics or automata theory, is to generate and demarcate the totality of grammatical constructions of a language, natural or automata oriented. A simple grammar for a fragment of English, determined by 12 rules (see ), can serve to introduce the main ideas.
In this simple grammar, each rule is of the form g → g′ (read, “g′ replaces g”) and has the meaning that g′ may be rewritten for g within strings of symbols. The symbol that appears in the rules may be understood as standing for the grammatical category “sentence,” for “pronoun,” for “verb phrase,” for “noun phrase,” and so forth. Symbols marked with a vinculum (-) constitute the set VN of nonterminal symbols. The English expressions “she,” etc., occurring in the rules constitute the set VT of terminal symbols. is the initial symbol.
Beginning with , sentences of English may be derived by applications of the rules. The derivation begins with ; the first rule allows to be rewritten for , yielding ; the fourth rule allows to be rewritten for , yielding ; and so forth (see ). A last step yields a terminal string or sentence; it consists solely of elements of the terminal vocabulary VT. None of the rules apply to it; so no further steps are possible.
The set of sentences thus generated by a grammar is called a language. Aside from trivial examples, grammars generate denumerably infinite languages.
Recursively enumerable grammars and Turing acceptors
As noted above, an elementary result of automata theory is that every recursively enumerable set constitutes an accepted set. Generally speaking, acceptors are two-way unbounded tape automata. On the other hand, a grammar consisting of rules g → g′, in which g and g′ are arbitrary words of (VT ∪ VN)*, is an unrestricted rewriting system, and any recursively enumerable set of words—i.e., language in the present sense—is generated by some such system. These very general grammars thus correspond to two-way acceptors, called Turing acceptors, that accept precisely the recursively enumerable sets.
Finite-state grammars and finite-state acceptors
Acceptors that move tape left only, reading symbol by symbol and erasing the while, are the simplest possible, the finite-state acceptors. These automata have exactly the same capability as McCulloch-Pitts automata and accept sets called regular sets. The corresponding grammars in the classification being discussed are the finite-state grammars. In these systems the rules g → g′ are restricted so that g is a nonterminal v of VN (as exemplified above) and g′ is of the form us, u ∊ VN and s ∊ VT. The languages generated by finite-state grammars, owing to this correspondence, are called regular languages.
Although these simple grammars and acceptors are of some interest in information theory and in neural network modelling, they are not descriptively adequate for English or for such standard computer languages as Algol because they are not able to account for phrase structure. In particular, finite-state grammars cannot generate self-embedded sentences such as “the man the dog bit ran away,” nor can they produce sentences with several readings such as “she is a pretty little girl.”