P. Wyard. Context free grammar induction using genetic algorithms. In Richard K. Belew and Lashon B. Booker, editors, Procceedings of the Fourth International Conference on Genetic Algorithms, pages 514--518, University of California - San Diego, La Jolla, CA, USA, 13-16 July 1991. Morgan Kaufmann.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....treat evolution of (stochastic) context free grammars and push down automata. Most of this research however does not deal with real linguistic data. Dupont, 1994) Huijsen, 1993) Kammeyer and Belew, 1996) Keller and Lutz, 1997a; Keller and Lutz, 1997b) Lucas, 1993; Lucas, 1994) Wyard, 1989; Wyard, 1991), Zhou and Grefenstette, 1986) but rather with constructed, arti cial languages (e.g. brackets, palindromes) In most cases, both positive and negative data are used and representation is usually some formal encoding of rules or rule sets. Achievements in this area can eventually be projected ....

Wyard, P. 1991. Context-free grammar induction using genetic algorithms. In R. Belew and L.B. Booker, editors, Proceedings of the Fourth International Conference on Genetic Algorithms, San Mateo. ICGA, Morgan Kaufmann.

....as follows: given a sample of strings from some language over an alphabet, Sigma , find a stochastic context free grammar which describes the language from which the strings were drawn. Some similar EA research has focused on nonstochastic context free grammars and on stochastic regular grammars[8, 9, 6]. Our previous work in this area used an EA and grammar encoding scheme similar to that used here[4] Before describing the details of the problem, our genotypic representation of grammars, and our fitness function, we give some general specifications of our EA. Our algorithm is panmictic and has ....

Peter Wyard. "Context Free Grammar Induction Using Genetic Algorithms", Proceedings of the Fourth International Conference on Genetic Algorithms. Morgan Kaufmann Publishers, Inc., San Francisco, CA, 1991.

....dependencies and constraints, has made it dicult to incorporate it in typically propositional evolutionary systems such as genetic algorithms. With the notable exception of Losee s LUST system (Losee, 1995) most GA syntactic research has focussed on non linguistic data. Smith and Witten (1996) Wyard (1991), Antonisse (1991) and Blasband (1998) are some examples on how Genetic Programming can be applied to the induction and optimization of simple grammars. But most of these systems are not suited to investigate the dynamics of grammar evolution itself, mainly because the grammatical system and ....

Wyard, P. 1991. Context free grammar induction using genetic algorithms. In Proc. 4th Int. Conf. on Genetic Algorithms., pages 514-518.

.... Shaw, 1994) to expertsystem rules (Montana, 1990) to weights for a game s evaluation function (Rendell, 1990) to weights and orientations for the k nearest neighbor algorithm (Kelly Davis, 1991; Punch et al. 1993) to finite state automata (Fogel et al. 1966) and context free grammars (Wyard, 1991), to production system like rules (Booker et al. 1989; De Jong et al. 1993; Greene Smith, 1993, 1994; Holland, 1986; Janikow, 1993) Financial Forecasting Using Genetic Algorithms 549 Higher level constructs such as neural networks and LISP programs are very powerful representations. However, ....

Wyard, P. 1991. Context free grammar induction using genetic algorithms. In Proceedings of the fourth international conference on genetic algorithms, 514518.

....of examples is missing, the problem is again NP hard (Angluin, 1978) 1. 3 Related Research A number of results have been reported for inference of regular and context free grammars with evolutionary techniques (e.g. Zhou Grefenstette (1986) Kammeyer Belew (1996) Lucas (1994) Dupont (1994) Wyard (1989) and (1991)) Schwehm Ost (1995) and Keller Lutz (1997a) and (1997b) describe results concerning the inference of stochastic grammars with genetic algorithms. Much of this research bases inference on both negative and positive examples, and no real linguistic data sets have been used. Genotype ....

P. Wyard. 1991. Context free grammar induction using genetic algorithms. In R. K. Belew and L. B. Booker, editors, Proceedings of the Fourth International Conference on Genetic Algorithms. Morgan Kaufmann.

....Steve, 896] Wilson, Stewart W. 207, 894] Winchell, Michael, 98] Wodak, Shoshana J. 876] Wong, Hermean, 622] Wong, K. P. 535] Wong, Y. W. 535] Wood, R. L. 840] Wu, Q. H. 828] Wu, X. 1072] Wu, Yu, 1051, 1084] Wu, Z. 911] Wurtz, Diethelm, 393, 394] Wyard, Peter, [1071] Wyckoff, R. O. 637] Xanthakis, Spyros, 1075] Xiao, Jing, 715] Xiao, Yong Liang (Leon) 1076] Xibilia, M. G. 156, 158] Xinhai, Chen, 1077] Xu, H. Y. 408] Yabuta, Tetsuro, 975] Yackel, Jonathan, 843, 844] Yamada, Shin ichi, 884] Yamada, Takayuki, 975] Yamada, T. 204] ....

.... [1035] Very Fast Simulated Re Annealing, 251] competition, 817] complexity, 45, 880] compression, 631, 700] computational geometry, 1084] triangulation, 1051] computer graphics, 617] computer networks, 562, 602] computer science viruses, 48] context free grammar induction, [1071] context free grammars, 110] control, 108, 125, 151, 192, 259, 280, 288, 292, 367, 436, 482, 543, 552, 554, 558, 608, 667, 711, 813, 906, 1009, 1017, 1061] control bio, 14] chemical reaction, 559] distributed systems, 511] environmental, 162] exhaust emissions, 728] fuzzy, 1044, ....

[Article contains additional citation context not shown here]

Peter Wyard. Context free grammar induction using genetic algorithms. In IEE Colloquium on `Grammatical Inference: Theory, Applications and Alternatives', volume Digest No. 092, Colchester, UK, 22.- 23. April 1993. IEE, London. y(CCA 44588/93) ga:Wyard93a.

.... a way of optimizing the Boolean expressions produced which are, generally, quite long, although we have some preliminary 30 results along this research path [12] Another possibility that we are considering is the use of genetic programming with a grammar representation to generate circuits [42, 43]. The use of a grammar representation seems to have several advantages, mainly because it can constrain the topology of the circuits produced without reducing in a significant way the generative power of the evolutionary technique. Some preliminary work developed by Jones and Joines [17] seems to ....

Peter Wyard. Context Free Grammar Induction Using Genetic Algorithms. In Richard K. Belew and Lashon B. Booker, editors, Proceedings 35 of the Fourth International Conference on Genetic Algorithms, pages 512--517, San Mateo, California, 1991. Morgan Kaufmann.

....performance and automata size. Svingen 1998) uses a GP on regular expressions. Regular expressions are directly encoded as program trees, and fitness is based on correct example classification. He successfully evolved the Tomita languages. Context free languages have also been studied. (Wyard 1991) uses a GA to evolve context free grammars. Chromosomes takes the form of lists of production rules, which guarantees correctness at all times. The fitness function scores example classification performance. Two simple CFG s were successfully evolved. Lankhorst 1994) uses a vector encoding to ....

Wyard, P. (1991). Context Free Grammar Induction Using Genetic Algorithms. In: Proceedings 4th International Conference on Genetic Algorithms. pp. 514--518.

....in a symbolic form. Thirdly, since a GA aims at continuously improving potential solutions, it should offer the possibility to rapidly converge to a new solution after updating the learning samples. A very preliminary work on the use of GA for grammatical inference has been recently proposed [17]. However, the theoretical framework was not stated, a lot of a priori knowledge was used (number of rules, maximal rule length, sets of terminals and nonterminals of the unknown grammar supposed to be known) and the experimental assessment was very limited. In the sequel, we detail the ....

P. Wyard, Context Free Grammar Induction Using Genetic Algorithms, Proc. of the 4th ICGA, Morgan Kaufmann Pub., CA, pp. 514-518, 1991.

....and to avoid poor solution areas in the search space altogether. Related Research A number of results have been reported for inference of regular and context free grammars with evolutionary techniques, e.g. by Zhou Grefenstette (1986) Kammeyer Belew (1996) Lucas (1994) Dupont (1994) Wyard (1989) and (1991). Results concerning the inference of stochastic grammars with genetic algorithms have been described by Schwehm Ost (1995) and Keller Lutz (1997a) and (1997b) describe. Much of this research bases inference on both negative and positive examples, and no real linguistic data sets have been ....

P. Wyard. 1991. Context free grammar induction using genetic algorithms. In Richard K.

....examples is missing, the problem is again NP hard (Angluin, 1978) 1. 3 Related Research A number of results have been reported for inference of regular and context free grammars with evolutionary techniques (e.g. Zhou Grefenstette (1986) Kammeyer Belew (1996) Lucas (1994) Dupont (1994) Wyard (1989) and (1991)) Schwehm Ost (1995) and Keller Lutz (1997a) and (1997b) describe results concerning the inference of stochastic grammars with genetic algorithms. Much of this research bases inference on both negative and positive examples, and no real linguistic data sets have been used. Genotype ....

P. Wyard. 1991. Context free grammar induction using genetic algorithms. In R. K. Belew and L. B. Booker, editors, Proceedings of the Fourth International Conference on Genetic Algorithms. Morgan Kaufmann.

....from the given terminals and nonterminals. The most difficult grammar learned using this approach is that for 2 symbol palindromes, which required chromosomes of 75 bits. Using what he calls embedded normal form to represent grammars (Lucas, 1994) he succeeded in learning 3 symbol palindromes. Wyard (1991) successfully uses GAs to infer GNF grammars for the language of correctly balanced and nested parentheses, but fails on the language of sentences containing equal numbers of a s and b s. A second paper by the same author (Wyard, 1994) describes positive results on the inference of two classes of ....

Wyard, P., 1991. Context free grammar induction using genetic algorithms, in R. Belew and L. Booker (eds), Proceedings of the Fourth International Conference on Genetic Algorithms ICGA'92, Morgan Kaufmann, San Mateo, CA.

.... this problem (for a survey, see [AS83] e.g. trying to induce finite state automata to accept regular languages [BP87] or to learn context free grammars directly from examples [VB87] Genetic algorithms have been applied to the induction of finite state automata [ZG86] context free grammars [Wya91] and push down automata [SJ92, Hui93] This paper presents a genetic algorithm that is used to infer context free grammars from legal and illegal examples of a context free language. University of Groningen, Dept. of Computing Science, P.O.Box 800, 9700 AV Groningen, The Netherlands, phone: ....

....use a low level binary representation of these rules, preferably in such a way that each bitstring is guaranteed to represent a legal production rule. The second is to take a high level representation in which each chromosome is a list of barely encoded production rules, such as the one used by [Wya91] or the marker based encoding of [Hui93] However, such a high level representation has a disadvantage over a binary representation. As was pointed out by Holland [Hol75] bitstrings can represent many more schemata than higher level representations, yielding a better coverage of the search ....

[Article contains additional citation context not shown here]

P. Wyard. Context free grammar induction using genetic algorithms. In R. Belew and L.B. Booker, editors, Proceedings of the Fourth International Conference on Genetic Algorithms ICGA'92, San Mateo, CA, 1991. Morgan Kaufmann.

....order. Of the 300 starting points tried, we found 300 different local minima. It should also be noted that none of the grammars found in the experiment were the correct grammar. This indicates that there are, in fact, a considerable number of local minima, and that this is indeed a problem. Wyard [8] found a similar problem with local minima in his genetic algorithm approach. In general, the incorrect grammars found in these experiments are characterized by large numbers of long rules (compared to the correct grammar) Some grammar learning schemes maximize not just the fit of the grammar to ....

Wyard, P. Context free grammar induction using genetic algorithms. Presented at Proceedings of the 4th International Conference on Genetic Algorithmss, San Mateo (1991 ).

....of robust, probabilistic optimization techniques that offer advantages over specialised procedures for automated grammatical inference. A number of researchers have already described applications of genetic algorithms to language identification problems with some success (Zhou Grefenstette 1986; Wyard 1991; Sen Janakiraman 1992; Angeline, Saunders Pollack 1993; Huijsen 1993; Lucas 1993; Dupont 1994; Lankhorst 1994; Dunay, Petry, Buckles 1994; Schwem Ost 1995) However, with the exception of work reported by Schwem and Ost (Schwem Ost 1995) the problem of inferring stochastic language ....

Wyard, P. (1991) Context-free grammar induction using genetic algorithms, in R.Belew and L.B. Booker (eds.), Proceedings of the Fourth International Conference on Genetic Algorithms, ICGA'92 , 514--418, Morgan Kaufmann. CA.

....of the individual genes is now profound: the flipping of a single bit (and the corresponding removal or addition of a production) can render a previously perfect grammar utterly useless. Perhaps as a result of these problems, only relatively simple (and deterministic) CFGs have been inferred (e.g. [3]) using GAs. Kitano [4] was perhaps the first to publish results on the effects of chromosome design of relevance to us here. His results compared the effects of using a direct encoding of a neural architecture (as a binary matrix indicating the presence or absence of a neuron) with using a ....

P. Wyard, "Context-free grammar induction using genetic algorithms," in Proceedings of the fourth international conference on Genetic Algorithms (R. Belew and L. Booker, eds.), pp. 514 -- 518, San Mateo, CA: Morgan Kaufman, (1991).

....effort has been directed towards applying GAs to the inference of context free grammars. Koza [6] outlined a GA for detecting exons of length 5 within DNA. After 35 generations, the resulting 61 node tree was 100 successful at identifying all exons in a segment of 1000 nucleiotide bases. Wyard [16] devised a genetic algorithm for the language of correctly balanced nested parentheses which successfully inferred a concise correct grammar from 20 test strings in just 3 generations. Wyard also constructed a GA for inferring the more complex language of all strings containing equal numbers of ....

Wyard, P. 1991. Context free grammar induction using genetic algorithms. In Proceedings of the 4th International Conference on Genetic Algorithms, 514--518.

....[Ho75] are a family of robust, probabilistic optimization techniques that offer advantages over specialised procedures for automated grammatical inference. A number of researchers have already described applications of genetic algorithms to language identification problems with some success [ZG86, Lu93, SJ92, La94, Wy91, DPB94, Hu93, SO95]. However, with the exception of recent work reported by Schwem and Ost [SO95] the problem of inferring stochastic language models has not been addressed. This is surprising in view of the many practical applications of such models to tasks including S A B (1:0) A a (0:6) A C S (0:4) B ....

Wyard, P. (1991) Context-free grammar induction using genetic algorithms, in R.Belew and L.B. Booker (eds.), Proceedings of the Fourth International Conference on Genetic Algorithms, ICGA'92 , 514--418, Morgan Kaufmann. CA.

....effort has been directed towards applying GAs to the inference of context free grammars. Koza (Koza 1992) outlined a GA for detecting exons of length 5 within DNA. After 35 generations, the resulting 61 node tree was 100 successful at identifying all exons in a segment of 1000 neucleoitide bases. Wyard (Wyard 1991) devised a genetic algorithm for the language of correctly balanced nested parentheses which successfully inferred a concise correct grammar from 20 test strings in just 3 generations. Wyard also constructed a GA for inferring the more complex language of all strings containing equal numbers of ....

Wyard, P. 1991. Context free grammar induction using genetic algorithms. In Proceedings of the 4th International Conference on Genetic Algorithms, 514--518.

No context found.

P. Wyard. Context free grammar induction using genetic algorithms. In Richard K. Belew and Lashon B. Booker, editors, Procceedings of the Fourth International Conference on Genetic Algorithms, pages 514--518, University of California - San Diego, La Jolla, CA, USA, 13-16 July 1991. Morgan Kaufmann.

No context found.

P. Wyard. Context free grammar induction using genetic algorithms. In Proc. of the 4th Int. Conf. on Genetic Algorithms, pages 514-518, 1991.

No context found.

P. Wyard. Context free grammar induction using genetic algorithms. In Proc. of the 4th Int. Conf. on Genetic Algorithms, pages 514--518, 1991.

No context found.

P. Wyard. Context-free grammar induction using genetic algorithms. In R. Belew and L.B. Booker, editors, Proceedings of the Fourth International Conference on Genetic Algorithms, pages 514--518, San Mateo, 1991. ICGA, Morgan Kaufmann.

No context found.

Wyard, P.: Context-free grammar induction using genetic algorithms. In Belew, R., Booker, L., eds.: Proceedings of the Fourth International Conference on Genetic Algorithms, San Mateo, ICGA, Morgan Kaufmann (1991) 514--518

No context found.

P. Wyard, "Context free grammar induction using genetic algorithms, " in Proceedings 4th International Conference on Genetic Algorithms, 1991, pp. 514--518.

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