On the Locality of Grammatical Evolution

It is well known that using high-locality representations is important for efficient evolutionary search. This paper investigates the locality of the genotype-phenotype mapping (representation) used in grammatical evolution (GE). The results show that the representation used in GE has problems with locality as many neighboring genotypes do not correspond to neighboring phenotypes. Experiments with a simple local search strategy reveal that the GE representation leads to lower performance for mutationbased search approaches in comparison to standard GP representations. The results suggest that locality issues should be considered for further development of the representation used in GE

Geometric Semantic Grammatical Evolution

This is the author accepted manuscript. The final version is available from Springer via the DOI in this record.Geometric Semantic Genetic Programming (GSGP) is a novel form of Genetic Programming (GP), based on a geometric theory of evolutionary algorithms, which directly searches the semantic space of programs. In this chapter, we extend this framework to Grammatical Evolution (GE) and refer to the new method as Geometric Semantic Grammatical Evolution (GSGE). We formally derive new mutation and crossover operators for GE which are guaranteed to see a simple unimodal fitness landscape. This surprising result shows that the GE genotypephenotype mapping does not necessarily imply low genotype-fitness locality. To complement the theory, we present extensive experimental results on three standard domains (Boolean, Arithmetic and Classifier)

Towards the Evolution of Multi-Layered Neural Networks: A Dynamic Structured Grammatical Evolution Approach

Current grammar-based NeuroEvolution approaches have several shortcomings. On the one hand, they do not allow the generation of Artificial Neural Networks (ANNs composed of more than one hidden-layer. On the other, there is no way to evolve networks with more than one output neuron. To properly evolve ANNs with more than one hidden-layer and multiple output nodes there is the need to know the number of neurons available in previous layers. In this paper we introduce Dynamic Structured Grammatical Evolution (DSGE): a new genotypic representation that overcomes the aforementioned limitations. By enabling the creation of dynamic rules that specify the connection possibilities of each neuron, the methodology enables the evolution of multi-layered ANNs with more than one output neuron. Results in different classification problems show that DSGE evolves effective single and multi-layered ANNs, with a varying number of output neurons

Complex systems in the history of American English

Kretzschmar 2009 has demonstrated that language in use, speech as opposed to linguistic systems as usually described by linguists, satisfies the conditions for complex systems as defined in sciences such as physics, evolutionary biology, and economics. This finding has strong methodological consequences for study of the history of American English. This paper discusses implications for the initial formation of American English and its varieties, with reference to Schneider 2007, as the product of random interactions between speakers of different input varieties of English. It also considers westward expansion of American dialects, with reference to Kretzschmar 1996, as an effect of proximity, especially along settlement routes. Finally, it describes how sociolinguistic discussions of more recent change should also be understood as occurring within the different intersecting scales of complex systems of speech in America

Parallel Distributed Grammar Engineering for Practical Applications

Based on a detailed case study of parallel grammar development distributed across two sites, we review some of the requirements for regression testing in grammar engineering, summarize our approach to systematic competence and performance profiling, and discuss our experience with grammar development for a commercial application. If possible, the workshop presentation will be organized around a software demonstration

Morphologically Conditioned Changes in Wanka-Quechua

published or submitted for publicationis peer reviewe

The source ambiguity problem: Distinguishing the effects of grammar and processing on acceptability judgments

Judgments of linguistic unacceptability may theoretically arise from either grammatical deviance or significant processing difficulty. Acceptability data are thus naturally ambiguous in theories that explicitly distinguish formal and functional constraints. Here, we consider this source ambiguity problem in the context of Superiority effects: the dispreference for ordering a wh-phrase in front of a syntactically “superior” wh-phrase in multiple wh-questions, e.g., What did who buy? More specifically, we consider the acceptability contrast between such examples and so-called D-linked examples, e.g., Which toys did which parents buy? Evidence from acceptability and self-paced reading experiments demonstrates that (i) judgments and processing times for Superiority violations vary in parallel, as determined by the kind of wh-phrases they contain, (ii) judgments increase with exposure, while processing times decrease, (iii) reading times are highly predictive of acceptability judgments for the same items, and (iv) the effects of the complexity of the wh-phrases combine in both acceptability judgments and reading times. This evidence supports the conclusion that D-linking effects are likely reducible to independently motivated cognitive mechanisms whose effects emerge in a wide range of sentence contexts. This in turn suggests that Superiority effects, in general, may owe their character to differential processing difficulty