The purpose of this paper is to give some insights into the immense role of Frege's first order logic (FOL) in the development of computer science. We argue that the FOL is fundamental in computer science, and that some computer science subfields could not have existed without their theoretical foundations built on this form of logic. Among these subfields, one can mention the Type Theory, Databases, Descriptive Complexity, Artificial Intelligence, Logic Programming, and Automated Theorem Proving. To illustrate our point, an in-depth attention will in particular be given to the foundational development of the most popular logic programming language, PROLOG, and the Automated Theorem Proving (ATP) systems. Importantly, when studying the interactions between logic and computer science in the literature, we can observe a significant gap in the provision of the appropriate abstraction level. Specifically, we often encounter two different levels of abstraction. The first of these is relatively high even when describing technical notions in computer science, which obviously produces a lack of precision. The second adopts a technical-oriented approach which easily makes the topic and discussion unintuitive or inaccessible to the non-specialist. The paper attempts to remedy these problems by adopting a balanced approach that provides a moderate level of abstraction that targets a deeper understanding of the topic without imposing a very technical presentation on the reader.
Meaning is the heart of language and it is its ultimate purpose; without the capacity to express meaning language is rendered as sequences of sounds or letters, and only when those sounds are judged capable of having a meaning do they qualify as language. Perceiving meaning does not solely depend on scrutinizing the literal sense of words, but it also comprises recognizing the meaning beyond language. From here, it can be inferred that when tackling meaning of utterances, two perspectives must be rendered: conceptual meaning, the literal or the core sense of a word also referred to as the denotative meaning and the associative meaning, which refers to aspects of the meaning that do not contribute to the denotation or concept of an expression and that do not change the range of possible referents (Murphy & Koskela, 2010). As a matter of fact, though English as foreign language learners, at the Lebanese University, do relish a wide vocabulary bank, and do know many of the words' meanings they encounter throughout their studies, they are, unfortunately, incapable of transferring their linguistic competence into semantic perception of comprehending the stylistic connotations of what they read. This can be traced to Lebanese University students' unawareness of the stylistic features of discourse which, in turn, is rendered as an impediment obstructing language processing. In this respect, via a comprehensive questionnaire, the study is meant to reflect a practical investigation on the perception of post graduates preparing for their master's degree in English at the Lebanese University, fifth branch, of stylistic features of words. The results depicted that stylistic features are not well perceived by EFL learners. Implications and recommendations for teachers, students, and curriculum designers were offered in the light of the study's findings.
The developments of an algebraic logical language of thoughts by G. Boole are considered using historical and theoretical perspectives. The technical implementations of Boolean logic in combinational circuits and in modern cryptography show strong influences of a 19th century logic on the latest technologies of computing.
The purpose of this paper is to show that inductive logic programming (ILP) is still relevant in contemporary machine learning applications. We mainly emphasize three modern applications where the use of ILP approach is particularly effective comparing to other machine learning methods. These applications are precisely related to search techniques, game strategies, and user behaviours on mobile areas.
In this article, we propose an initial formal model of computationalism based on mathematical relations between cognition and computation. More specifically, based on a set of cognitive constituents as a domain, and a set of computational implementations as a range, we define two relations of transformation over these sets. Moreover, we define the principles of implementability, describability, and phenomena correspondence, and we conjecture that full computationalism does not hold since these principles are not fulfilled. Particularly, many cognitively-tied phenomena fail to respect the describability principle which is necessary for representing a cognitive state by a computational state.
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