A spatially-structured PCG method for content diversity in a Physics-based simulation game

This paper presents a spatially-structured evolutionary algorithm (EA) to procedurally generate game maps of di ferent levels of di ficulty to be solved, in Gravityvolve!, a physics-based simulation videogame that we have implemented and which is inspired by the n- body problem, a classical problem in the fi eld of physics and mathematics. The proposal consists of a steady-state EA whose population is partitioned into three groups according to the di ficulty of the generated content (hard, medium or easy) which can be easily adapted to handle the automatic creation of content of diverse nature in other games. In addition, we present three fitness functions, based on multiple criteria (i.e:, intersections, gravitational acceleration and simulations), that were used experimentally to conduct the search process for creating a database of maps with di ferent di ficulty in Gravityvolve!.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Linguistic identifiers of L1 Persian speakers writing in English:NLID for authorship analysis

This research focuses on Native Language Identification (NLID), and in particular, on the linguistic identifiers of L1 Persian speakers writing in English. This project comprises three sub-studies; the first study devises a coding system to account for interlingual features present in a corpus of L1 Persian speakers blogging in English, and a corpus of L1 English blogs. Study One then demonstrates that it is possible to use interlingual identifiers to distinguish authorship by L1 Persian speakers. Study Two examines the coding system in relation to the L1 Persian corpus and a corpus of L1 Azeri and L1 Pashto speakers. The findings of this section indicate that the NLID method and features designed are able to discriminate between L1 influences from different languages. Study Three focuses on elicited data, in which participants were tasked with disguising their language to appear as L1 Persian speakers writing in English. This study indicated that there was a significant difference between the features in the L1 Persian corpus, and the corpus of disguise texts. The findings of this research indicate that NLID and the coding system devised have a very strong potential to aid forensic authorship analysis in investigative situations. Unlike existing research, this project focuses predominantly on blogs, as opposed to student data, making the findings more appropriate to forensic casework data

A Multi-Step Analysis of the Evolution of English Do-Support

This dissertation advances our understanding of the historical evolution and grammatical structure of English do-support through the application of novel historical data to this classical problem in historical syntax. Do-support is the phenomenon in English whereby a pleonastic auxiliary verb do is inserted in certain clause types. The phenomenon is characteristic of the modern language, and there is robust evidence that it emerged beginning in roughly the year 1500. The fine quantitative details of this emergence and the variation it engendered have been an object of study since Ellegård (1953). From the standpoint of generative grammar, Roberts (1985), Kroch (1989), and many others have treated the emergence of do-support as a closely-following consequence of the loss of V-to-T raising in the 15th and 16th centuries. Taking a cross-linguistic perspective, I show that though the totality of English do-support is uncommon in other languages, the phenomenon may be seen as the combination of several discrete building blocks, each of which is robustly attested. From this perspective, a question is raised about the genesis of English do-support: given that the present-day phenomenon is evidently composed of several separate subcases, why should its cause be attributed solely to the loss of V-to-T raising? I argue that the earliest emergence of do-support in English is in fact attributable to a different source: a usage of do as a marker of external arguments. This explanation addresses the following points, which under earlier accounts were unexplained: * The different behavior of do-support across argument structure types. * The appearance of do-support in affirmative declaratives at a peak rate of 10%, much more than can be attributed to emphatic assertions. * The emergence of do-support from a Middle English causative. This intermediate do spread through the language until roughly 1575, when the loss of verb raising triggered an abrupt reanalysis which transformed the argument-structure marking do into its modern form

Cognition-based approaches for high-precision text mining

This research improves the precision of information extraction from free-form text via the use of cognitive-based approaches to natural language processing (NLP). Cognitive-based approaches are an important, and relatively new, area of research in NLP and search, as well as linguistics. Cognitive approaches enable significant improvements in both the breadth and depth of knowledge extracted from text. This research has made contributions in the areas of a cognitive approach to automated concept recognition in. Cognitive approaches to search, also called concept-based search, have been shown to improve search precision. Given the tremendous amount of electronic text generated in our digital and connected world, cognitive approaches enable substantial opportunities in knowledge discovery. The generation and storage of electronic text is ubiquitous, hence opportunities for improved knowledge discovery span virtually all knowledge domains. While cognition-based search offers superior approaches, challenges exist due to the need to mimic, even in the most rudimentary way, the extraordinary powers of human cognition. This research addresses these challenges in the key area of a cognition-based approach to automated concept recognition. In addition it resulted in a semantic processing system framework for use in applications in any knowledge domain. Confabulation theory was applied to the problem of automated concept recognition. This is a relatively new theory of cognition using a non-Bayesian measure, called cogency, for predicting the results of human cognition. An innovative distance measure derived from cogent confabulation and called inverse cogency, to rank order candidate concepts during the recognition process. When used with a multilayer perceptron, it improved the precision of concept recognition by 5% over published benchmarks. Additional precision improvements are anticipated. These research steps build a foundation for cognition-based, high-precision text mining. Long-term it is anticipated that this foundation enables a cognitive-based approach to automated ontology learning. Such automated ontology learning will mimic human language cognition, and will, in turn, enable the practical use of cognitive-based approaches in virtually any knowledge domain --Abstract, page iii

Visualising Time

This study investigates the visualisation of temporal relationships between objects. A popular method employed for such information visualisations is the time line consisting of a single horizontal axis along which temporal events or objects are depicted at specific points or intervals. The orientation of the temporal progression along the axis line will generally coincide with the orientation of the literary writing progression of the culture and language. For example a time line visualised in a Western culture with English as its literary base will exhibit a temporal progression orientation of early/left, later/right whereas Arabian culture with an Arabic literary base will exhibit the reverse temporal progression orientation. In both cultures and languages temporal metaphor use spatial concepts to describe temporal relationships with no discourse to transversal orientation. This is reflected by never hearing the phrase “the months to the right” but rather “the months ahead”. In science, Einstein showed via his special and general theories of relativity that time and space are interlinked. The scientific rationalisation of time and space along with the use of spatial concepts as temporal metaphor implies that the underlying perception of time is spatial. Information visualisations are the externalisations of our perceptions. Therefore temporal information visualisations should employ spatial visualisation techniques. This study evaluated spatial visualisation techniques for temporal information visualisations via a web survey. The spatial temporal information visualisations used in the survey employed no temporal cues such as time or date stamps but conferred all temporal progression via spatial cues. The findings from the analysis of the participant responses to the survey showed that spatial cues do impart temporal cues for temporal relationships

World to Word: Nomenclature Systems of Color and Species

As the digitization of information accelerates, the push to encode our surrounding numerically instead of linguistically increases. The role that language has traditionally played in the nomenclature of an integrative taxonomy is being replaced by the numeric identification of one or few quantitative characteristics. Nineteenth-century scientific systems of color identification divided, grouped, and named colors according to multiple characteristics. Now color identification relies on numeric values applied to spectrographic readings. This means of identification of color lacks the taxonomic rigor of nineteenth century systems. Identifying color by numeric value instead of by grouping and naming them, strips color taxonomy of all but one quantitative aspect of a color. I use the case of color taxonomy to argue against a similar trend of numeric identification in the biological sciences. Unlike historically more integrative approaches to taxonomy in biology, genomic sequencing identifies one or few quantitative characteristics to encode an organism. If genomic sequencing becomes the primary means of identification in the biological sciences, just as in numeric systems of color identification, scientific taxonomy would suffer. Basing my analysis on theories of perception of division and on theories of language, I use the cases of color and species to argue for the advantages of an integrative taxonomic system of naming and categorizing over a method of identification, which encodes limited characteristics numerically. I hold that language is the most sophisticated tool for systematic taxonomy and that taxonomic nomenclature should be retained