Applications of Evolutionary Algorithms in Formal Languages

Starting from the model proposed by means of Grammatical Evolution, we extend the applicability of the parallel and cooperative searching processes of Evolutionary Algorithms to a new topic: Tree Adjoining Grammar parsing. We evolved derived trees using a string-tree-representation.We also used a linear matching function to compare the yield of a derived tree with a given input. The running tests presented several encouraging results. A post running analysis allowed us to propose several research directions for extending the currently known computational mechanisms in the mildly context sensitive class of languages

On the learning of vague languages for syntactic pattern recognition

The method of the learning of vague languages which represent distorted/ambiguous patterns is proposed in the paper. The goal of the method is to infer the quasi-context-sensitive string grammar which is used in our model as the generator of patterns. The method is an important component of the multi-derivational model of the parsing of vague languages used for syntactic pattern recognition

Second CLIPS Conference Proceedings, volume 1

Topics covered at the 2nd CLIPS Conference held at the Johnson Space Center, September 23-25, 1991 are given. Topics include rule groupings, fault detection using expert systems, decision making using expert systems, knowledge representation, computer aided design and debugging expert systems

An Incremental Algorithm for Transition-based CCG Parsing

Incremental parsers have potential advantages for applications like language modeling for machine translation and speech recognition. We describe a new algorithm for incremental transition-based Combinatory Categorial Grammar parsing. As English CCGbank derivations are mostly right branching and non-incremental, we design our algorithm based on the dependencies resolved rather than the derivation. We introduce two new actions in the shift-reduce paradigm based on the idea of 'revealing' (Pareschi and Steedman, 1987) the required information during parsing. On the standard CCGbank test data, our algorithm achieved improvements of 0.88% in labeled and 2.0% in unlabeled F-score over a greedy non-incremental shift-reduce parser.11 page(s

Building a poker playing agent based on game logs using supervised learning

Tese de mestrado integrado. Engenharia Informática e Computação. Faculdade de Engenharia. Universidade do Porto. 201