A Formal Model of Metaphor in Frame Semantics

A formal model of metaphor is introduced. It models metaphor, first, as an interaction of “frames” according to the frame semantics, and then, as a wave function in Hilbert space. The practical way for a probability distribution and a corresponding wave function to be assigned to a given metaphor in a given language is considered. A series of formal definitions is deduced from this for: “representation”, “reality”, “language”, “ontology”, etc. All are based on Hilbert space. A few statements about a quantum computer are implied: The sodefined reality is inherent and internal to it. It can report a result only “metaphorically”. It will demolish transmitting the result “literally”, i.e. absolutely exactly. A new and different formal definition of metaphor is introduced as a few entangled wave functions corresponding to different “signs” in different language formally defined as above. The change of frames as the change from the one to the other formal definition of metaphor is interpreted as a formal definition of thought. Four areas of cognition are unified as different but isomorphic interpretations of the mathematical model based on Hilbert space. These are: quantum mechanics, frame semantics, formal semantics by means of quantum computer, and the theory of metaphor in linguistics

Perspectives on the Neuroscience of Cognition and Consciousness

The origin and current use of the concepts of computation, representation and information in Neuroscience are examined and conceptual flaws are identified which vitiate their usefulness for addressing problems of the neural basis of Cognition and Consciousness. In contrast, a convergence of views is presented to support the characterization of the Nervous System as a complex dynamical system operating in the metastable regime, and capable of evolving to configurations and transitions in phase space with potential relevance for Cognition and Consciousness

Polysemy and word meaning: an account of lexical meaning for different kinds of content words

There is an ongoing debate about the meaning of lexical words, i.e., words that contribute with content to the meaning of sentences. This debate has coincided with a renewal in the study of polysemy, which has taken place in the psycholinguistics camp mainly. There is already a fruitful interbreeding between two lines of research: the theoretical study of lexical word meaning, on the one hand, and the models of polysemy psycholinguists present, on the other. In this paper I aim at deepening on this ongoing interbreeding, examine what is said about polysemy, particularly in the psycholinguistics literature, and then show how what we seem to know about the representation and storage of polysemous senses affects the models that we have about lexical word meaning

Making meaning: developing an understanding of form in distance design education

Design education throughout the world provides students with a variety of experiences that help them develop an understanding of form and shape. The conventional model of such education requires students to participate in studio and workshop-based projects to develop skills through the creation of models and prototypes. However, with the increase in distance education worldwide we need to explore new ways for students to create and manipulate form remotely. This paper presents new work at the Open University, UK which set out to engage design students in form-making from a distance. Participants were given access to technical and design support that took rough sketches of chair designs and converted these into tangible scale models which were mailed back to the students. Several cycles of this activity generated data on how such supported modelling activity stimulated students' creative ability, design knowledge and motivation. This paper proposes new priorities for distance design education

Learning Language from a Large (Unannotated) Corpus

A novel approach to the fully automated, unsupervised extraction of dependency grammars and associated syntax-to-semantic-relationship mappings from large text corpora is described. The suggested approach builds on the authors' prior work with the Link Grammar, RelEx and OpenCog systems, as well as on a number of prior papers and approaches from the statistical language learning literature. If successful, this approach would enable the mining of all the information needed to power a natural language comprehension and generation system, directly from a large, unannotated corpus.Comment: 29 pages, 5 figures, research proposa

I'm sorry to say, but your understanding of image processing fundamentals is absolutely wrong

The ongoing discussion whether modern vision systems have to be viewed as visually-enabled cognitive systems or cognitively-enabled vision systems is groundless, because perceptual and cognitive faculties of vision are separate components of human (and consequently, artificial) information processing system modeling.Comment: To be published as chapter 5 in "Frontiers in Brain, Vision and AI", I-TECH Publisher, Viena, 200

Lexical Pragmatics : Relevance Theory and Generalized Conversational Implicatures

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