In this paper, a new approach to grammatical evolution is presented. The aim is to generate complete programs using probabilistic modeling and sampling of (probability) distribution of given grammars. To be exact, probabilistic context free grammars are employed and a modified mapping process is developed to create new individuals from the distribution of grammars. To consider problem structures in the individual generation, conditional dependencies between production rules are incorporated into the mapping process. Experiments confirm that the proposed algorithm is more effective than existing methods.

In this paper, we introduce a parallel algorithm for parsing context-free languages. Our algorithm can handle arbitrary context-free grammars since it is based on Earley's algorithm. Our algorithm can operate on any loosely coupled multiprocessor which can provide a topology of a one-way ring. Our algorithm uses p processors to parse an input string of length n where 1 p n. It is shown that our algorithm requires O(n3/p) time. The algorithm uses a simple job allocation strategy. However, it achieves high load balancing and uses the processors efficiently.

Finite state translation systems (fsts') are a widely studied computational model in the area of tree automata theory. In this paper, the string generating capacities of fsts' and their subclasses are studied. First, it is shown that the class of string languages generated by deterministic fsts' equals to that of parallel multiple context-free grammars, which are an extension of context-free grammars. As a corollary, it can be concluded that the recognition problem for a deterministic fsts is solvable in O(ne1)-time, where n is the length of an input word and e is a constant called the degree of the deterministic fsts'. In contrast to the latter fact, it is also shown that nondeterministic monadic fsts' with state-bound 2 can generate an NP-complete language.

CFGs (context-free grammars) with various types of memory are introduced and their generative capacities are investigated. For an automata-theoretic characterization, a new type of automaton called partitioning automaton is introduced and it is shown that the class of languages generated by CFGs with memory type X is equal to the class of languages accepted by partitioning automata of type X.

Parallel multiple context-free grammars (pmcfg's) and multiple context-free grammars (mcfg's) were introduced as extensions of context-free grammars to describe the syntax of natural languages. Pmcfg's and mcfg's deal with tuples of strings, and it has been shown that the universal recognition problem for mcfg's is EXP-POLY time-complete where the universal recognition problem is the problem to decide whether G generates w for a given grammar G and string w. In this paper, the universal recognition problems for the class of pmcfg's and for the subclass of pmcfg's with the information-lossless condition are shown to be EXP-POLY time-complete and PSPACE-complete, respectively. It is also shown that the problems for pmcfg's and for mcfg's with a bounded dimension are both -complete and those for pmcfg's and for mcfg's with a bounded degree are both -complete. As a corollary, the problem for modified head grammars introduced by Vijay-Shanker, et al. to define the syntax of natural languages is shown to be in deterministic polynomial time.

Multiple context-free grammars (mcfg's) are a subclass of generalized context-free grammars introduced by Pollard in order to describe the syntax of natural languages. First, this paper shows that the universal recognition problem for mcfg's is EXP-POLY time-complete, where the universal recognition problem is the one to decide whether G generates w for a given grammar G and string w. Next, it is shown that the problem for linear context-free rewriting systems introduced by Vijay-Shanker et al., which is a proper subclass of mcfg's, is PSPACE-complete.