Developments from enquiries into the learnability of the pattern languages from positive data

AbstractThe pattern languages are languages that are generated from patterns, and were first proposed by Angluin as a non-trivial class that is inferable from positive data [D. Angluin, Finding patterns common to a set of strings, Journal of Computer and System Sciences 21 (1980) 46–62; D. Angluin, Inductive inference of formal languages from positive data, Information and Control 45 (1980) 117–135]. In this paper we chronologize some results that developed from the investigations on the inferability of the pattern languages from positive data

The place of expert systems in business now and over the next decade

Information technology has entered a new generation. In recent years, considerable interest has been focussed on the commercialisation of expert systems, which represent an important application of Artificial Intelligence in the field of Information Technology. Expert systems are now in a crucial stage of development because, although in business computerised systems are not new, expert systems still need time for their applicability and usefulness to be proved. The market for expert systems will not develop if such systems are unable to cope with the demanding applications of business; for example with top management problem-solving and decision-making. This thesis is principally concerned with determining the position of expert systems in business by looking at these major business related issues. [Continues.

Extracting proofs from documents

Often, theorem checkers like PVS are used to check an existing proof, which is part of some document. Since there is a large difference between the notations used in the documents and the notations used in the theorem checkers, it is usually a laborious task to convert an existing proof into a format which can be checked by a machine. In the system that we propose, the author is assisted in the process of converting an existing proof into the PVS language and having it checked by PVS. 1 Introduction The now-classic ALGOL 60 report [5] recognized three different levels of language: a reference language, a publication language and several hardware representations, whereby the publication language was intended to admit variations on the reference language and was to be used for stating and communicating processes. The importance of publication language ---often referred to nowadays as "pseudo-code"--- is difficult to exaggerate since a publication language is the most effective way..

Learning categorial grammars

In 1967 E. M. Gold published a paper in which the language classes from the Chomsky-hierarchy were analyzed in terms of learnability, in the technical sense of identification in the limit. His results were mostly negative, and perhaps because of this his work had little impact on linguistics. In the early eighties there was renewed interest in the paradigm, mainly because of work by Angluin and Wright. Around the same time, Arikawa and his co-workers refined the paradigm by applying it to so-called Elementary Formal Systems. By making use of this approach Takeshi Shinohara was able to come up with an impressive result; any class of context-sensitive grammars with a bound on its number of rules is learnable. Some linguistically motivated work on learnability also appeared from this point on, most notably Wexler & Culicover 1980 and Kanazawa 1994. The latter investigates the learnability of various classes of categorial grammar, inspired by work by Buszkowski and Penn, and raises some interesting questions. We follow up on this work by exploring complexity issues relevant to learning these classes, answering an open question from Kanazawa 1994, and applying the same kind of approach to obtain (non)learnable classes of Combinatory Categorial Grammars, Tree Adjoining Grammars, Minimalist grammars, Generalized Quantifiers, and some variants of Lambek Grammars. We also discuss work on learning tree languages and its application to learning Dependency Grammars. Our main conclusions are: - formal learning theory is relevant to linguistics, - identification in the limit is feasible for non-trivial classes, - the `Shinohara approach' -i.e., placing a numerical bound on the complexity of a grammar- can lead to a learnable class, but this completely depends on the specific nature of the formalism and the notion of complexity. We give examples of natural classes of commonly used linguistic formalisms that resist this kind of approach, - learning is hard work. Our results indicate that learning even `simple' classes of languages requires a lot of computational effort, - dealing with structure (derivation-, dependency-) languages instead of string languages offers a useful and promising approach to learnabilty in a linguistic contex

Simple low cost causal discovery using mutual information and domain knowledge

PhDThis thesis examines causal discovery within datasets, in particular observational datasets where normal experimental manipulation is not possible. A number of machine learning techniques are examined in relation to their use of knowledge and the insights they can provide regarding the situation under study. Their use of prior knowledge and the causal knowledge produced by the learners are examined. Current causal learning algorithms are discussed in terms of their strengths and limitations. The main contribution of the thesis is a new causal learner LUMIN that operates with a polynomial time complexity in both the number of variables and records examined. It makes no prior assumptions about the form of the relationships and is capable of making extensive use of available domain information. This learner is compared to a number of current learning algorithms and it is shown to be competitive with them

Programming Paradigms, Information Types and Graphical Representations: Empirical Investigations of Novice Program Comprehension.

Centre for Intelligent Systems and their ApplicationsThis thesis describes research into the role of various factors in novice program comprehension, including the underlying programming paradigm, the representational features of the programming language, and the various types of information which can be derived from the program. The main postulate of the thesis is that there is no unique method for understanding programs, and that program comprehension will be influenced by, among other things, the way in which programs are represented, both semantically and syntactically. This idea has implications for the learning of programming, particularly in terms of how theses concepts should be embodied. The thesis is focused around three empirical studies. The first study, based on th so-called "information types" studies, challenged the idea that program comprehension is an invariant process over languages, and suggested that programming language will have a differential effect on comprehension, as evidenced by the types of information which novices are able to extract from a program. Despite the use of a markedly different language from earliier studies, the results were broadly similar. However, it was suggested that there are other factors additional to programming notation which intervene in the comprehension process, and which cannot be discounted. Furthermore, the study highlighted the need to tie the hypotheses about information extraction more closely to the programming paradigm. The second study introduced a graphical component into the investigation, and looked at the way in which visual representations of programs combine with programming paradigm to influence comprehension. The mis-match conjecture, which suggests that tasks requiring information which is highlighted by a notation will be facilitated relative to tasks where the information must be inferred, was applied to programming paradigm. The study showed that the mis-match effect can be overridden by other factors, most notably subjects' prior experience and the programming culture in which they are taught. The third study combined the methodologies of the first two studies to look at the mis-match conjecture within the wider context of information types. Using graphical representations of the control flow and data flow paradigms, it showed that, despite a bias toward one paradigm based on prior experience and culture, programming paradigm does influence the way in which the program is understood, resulting in improved performance on tasks requiring information which the paradigm is hypothesised to highlight. Furthermore, this effect extends to groups of information which could be said to be theoretically related to the information being highlighted. The thesis also proposes a new and more precise methodology for the analysis of students' accounts of their comprehension of a program, a form a data which is typically derived from the information types studies. It then shows how an analysis of this qualitative data can be used to provide further support for the quantitative results. Finally, the thesis suggests how the core results could be used to develop computer based support environments for novice visual programming, and provides other suggestions for further work

Programmiersprachen und Rechenkonzepte

Seit 1984 veranstaltet die GI-Fachgruppe "Programmiersprachen und Rechenkonzepte" regelmäßig im Frühjahr einen Workshop im Physikzentrum Bad Honnef. Das Treffen dient in erster Linie dem gegenseitigen Kennenlernen, dem Erfahrungsaustausch, der Diskussion und der Vertiefung gegenseitiger Kontakte. In diesem Forum werden Vorträge und Demonstrationen sowohl bereits abgeschlossener als auch noch laufender Arbeiten vorgestellt, unter anderem (aber nicht ausschließlich) zu Themen wie - Sprachen, Sprachparadigmen - Korrektheit von Entwurf und Implementierung - Werkzeuge - Software-/Hardware-Architekturen - Spezifikation, Entwurf - Validierung, Verifikation - Implementierung, Integration - Sicherheit (Safety und Security) - eingebettete Systeme - hardware-nahe Programmierung. In diesem Technischen Bericht sind einige der präsentierten Arbeiten zusammen gestellt