Merging two Hierarchies of Internal Contextual Grammars with Subregular Selection

In this paper, we continue the research on the power of contextual grammars with selection languages from subfamilies of the family of regular languages. In the past, two independent hierarchies have been obtained for external and internal contextual grammars, one based on selection languages defined by structural properties (finite, monoidal, nilpotent, combinational, definite, ordered, non-counting, power-separating, suffix-closed, commutative, circular, or union-free languages), the other one based on selection languages defined by resources (number of non-terminal symbols, production rules, or states needed for generating or accepting them). In a previous paper, the language families of these hierarchies for external contextual grammars were compared and the hierarchies merged. In the present paper, we compare the language families of these hierarchies for internal contextual grammars and merge these hierarchies.Comment: In Proceedings NCMA 2023, arXiv:2309.07333. arXiv admin note: text overlap with arXiv:2309.02768, arXiv:2208.1472

A sequence-length sensitive approach to learning biological grammars using inductive logic programming.

This thesis aims to investigate if the ideas behind compression principles, such as the Minimum Description Length, can help us to improve the process of learning biological grammars from protein sequences using Inductive Logic Programming (ILP). Contrary to most traditional ILP learning problems, biological sequences often have a high variation in their length. This variation in length is an important feature of biological sequences which should not be ignored by ILP systems. However we have identified that some ILP systems do not take into account the length of examples when evaluating their proposed hypotheses. During the learning process, many ILP systems use clause evaluation functions to assign a score to induced hypotheses, estimating their quality and effectively influencing the search. Traditionally, clause evaluation functions do not take into account the length of the examples which are covered by the clause. We propose L-modification, a way of modifying existing clause evaluation functions so that they take into account the length of the examples which they learn from. An empirical study was undertaken to investigate if significant improvements can be achieved by applying L-modification to a standard clause evaluation function. Furthermore, we generally investigated how ILP systems cope with the length of examples in training data. We show that our L-modified clause evaluation function outperforms our benchmark function in every experiment we conducted and thus we prove that L-modification is a useful concept. We also show that the length of the examples in the training data used by ILP systems does have an undeniable impact on the results

DIRECTIONAL HARMONIC SERIALISM

This dissertation proposes a novel phonological framework, directional Harmonic Serialism, that synthesizes constraint-based, rule-based, and formal language theoretic approaches to phonology. I illustrate its advantages in the domains of feature spreading, quantity-insensitive footing, and autosegmental phonology. Specifically, I demonstrate that across these disparate domains, directional Harmonic Serialism makes empirical predictions that more tightly model natural language phonology than alternative theories and that it does so using fewer theoretical mechanisms. At a high level, the theory outperforms alternatives using a simpler, more restricted toolkit

Head-Driven Phrase Structure Grammar

Head-Driven Phrase Structure Grammar (HPSG) is a constraint-based or declarative approach to linguistic knowledge, which analyses all descriptive levels (phonology, morphology, syntax, semantics, pragmatics) with feature value pairs, structure sharing, and relational constraints. In syntax it assumes that expressions have a single relatively simple constituent structure. This volume provides a state-of-the-art introduction to the framework. Various chapters discuss basic assumptions and formal foundations, describe the evolution of the framework, and go into the details of the main syntactic phenomena. Further chapters are devoted to non-syntactic levels of description. The book also considers related fields and research areas (gesture, sign languages, computational linguistics) and includes chapters comparing HPSG with other frameworks (Lexical Functional Grammar, Categorial Grammar, Construction Grammar, Dependency Grammar, and Minimalism)

Head-Driven Phrase Structure Grammar

Head-Driven Phrase Structure Grammar (HPSG) is a constraint-based or declarative approach to linguistic knowledge, which analyses all descriptive levels (phonology, morphology, syntax, semantics, pragmatics) with feature value pairs, structure sharing, and relational constraints. In syntax it assumes that expressions have a single relatively simple constituent structure. This volume provides a state-of-the-art introduction to the framework. Various chapters discuss basic assumptions and formal foundations, describe the evolution of the framework, and go into the details of the main syntactic phenomena. Further chapters are devoted to non-syntactic levels of description. The book also considers related fields and research areas (gesture, sign languages, computational linguistics) and includes chapters comparing HPSG with other frameworks (Lexical Functional Grammar, Categorial Grammar, Construction Grammar, Dependency Grammar, and Minimalism)

Recursion in cognition: a computational investigation into the representation and processing of language

La recursividad entendida como auto-referencia se puede aplicar a varios constructos de las ciencias cognitivas, como las definiciones teóricas, los procedimientos mecánicos, los procesos de cálculo (sean éstos abstractos o concretos) o las estructuras. La recursividad es una propiedad central tanto del procedimiento mecánico que subyace a la facultad del lenguaje como de las estructuras que esta facultad genera. Sin embargo, tanto las derivaciones sintácticas de la gramática, que constituyen un proceso computacional abstracto, como las estrategias de procesamiento del parser, que son un proceso en tiempo real, proceden de forma iterativa, lo cual sugiere que la especificación recursiva de un algoritmo se implementa de forma iterativa. Además, la combinación de la recursividad con las unidades léxicas y las imposiciones de los interfaces con los que la facultad del lenguaje interactúa resulta en un conjunto de estructuras sui generis que no tienen parangón en otros dominios cognitivos.Recursion qua self-reference applies to various constructs within the cognitive sciences, such as theoretical definitions, mechanical procedures (or algorithms), (abstract or real-time) computational processes and structures. Recursion is an intrinsic property of both the mechanical procedure underlying the language faculty and the structures this faculty generates. However, the recursive nature of the generated structures and the recursive character of the processes need to be kept distinct, their study meriting individual treatment. In fact, the nature of both the syntactic derivations of the grammar (an abstract computational process) and the processing strategies of the parser (a real-time process) are iterative, which suggests that recursively-defined algorithms are implemented iteratively in linguistic cognition. Furthermore, the combination of recursion, lexical items and the impositions of the interfaces the language faculty interacts with results in a sui generis set of structures with which other domains of the mind bear the most superficial of relations