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

Challenging the Computational Metaphor: Implications for How We Think

This paper explores the role of the traditional computational metaphor in our thinking as computer scientists, its influence on epistemological styles, and its implications for our understanding of cognition. It proposes to replace the conventional metaphor--a sequence of steps--with the notion of a community of interacting entities, and examines the ramifications of such a shift on these various ways in which we think

Understanding analogical reasoning : viewpoints from psychology and related disciplines

Analogy and metaphor have a long history of study in linguistics, education, philosophy and psychology. Consensus over what analogy is or how analogy functions in language and thought, however, has been elusive. This paper, the first in a two part series, examines these various research traditions, attempting to bring out major lines of agreement over the role of analogy in individual human experience. As well as being a general literature review which may be helpful for newcomers to the study of analogy, this paper attempts to extract from these literatures existing theories, models and concepts which may be interesting or useful for computational studies of analogical reasoning

Theories about architecture and performance of multi-agent systems

Multi-agent systems are promising as models of organization because they are based on the idea that most work in human organizations is done based on intelligence, communication, cooperation, and massive parallel processing. They offer an alternative for system theories of organization, which are rather abstract of nature and do not pay attention to the agent level. In contrast, classical organization theories offer a rather rich source of inspiration for developing multi-agent models because of their focus on the agent level. This paper studies the plausibility of theoretical choices in the construction of multi-agent systems. Multi-agent systems have to be plausible from a philosophical, psychological, and organizational point of view. For each of these points of view, alternative theories exist. Philosophically, the organization can be seen from the viewpoints of realism and constructivism. Psychologically, several agent types can be distinguished. A main problem in the construction of psychologically plausible computer agents is the integration of response function systems with representational systems. Organizationally, we study aspects of the architecture of multi-agent systems, namely topology, system function decomposition, coordination and synchronization of agent processes, and distribution of knowledge and language characteristics among agents. For each of these aspects, several theoretical perspectives exist.

Information and Experience in Metaphor: A Perspective From Computer Analysis

Novel linguistic metaphor can be seen as the assignment of attributes to a topic through a vehicle belonging to another domain. The experience evoked by the vehicle is a significant aspect of the meaning of the metaphor, especially for abstract metaphor, which involves more than mere physical similarity. In this article I indicate, through description of a specific model, some possibilities as well as limitations of computer processing directed toward both informative and experiential/affective aspects of metaphor. A background to the discussion is given by other computational treatments of metaphor analysis, as well as by some questions about metaphor originating in other disciplines. The approach on which the present metaphor analysis model is based is consistent with a theory of language comprehension that includes both the intent of the originator and the effect on the recipient of the metaphor. The model addresses the dual problem of (a) determining potentially salient properties of the vehicle concept, and (b) defining extensible symbolic representations of such properties, including affective and other connotations. The nature of the linguistic analysis underlying the model suggests how metaphoric expression of experiential components in abstract metaphor is dependent on the nominalization of actions and attributes. The inverse process of undoing such nominalizations in computer analysis of metaphor constitutes a translation of a metaphor to a more literal expression within the metaphor-nonmetaphor dichotomy

The effect of multiple knowledge sources on learning and teaching

Current paradigms for machine-based learning and teaching tend to perform their task in isolation from a rich context of existing knowledge. In contrast, the research project presented here takes the view that bringing multiple sources of knowledge to bear is of central importance to learning in complex domains. As a consequence teaching must both take advantage of and beware of interactions between new and existing knowledge. The central process which connects learning to its context is reasoning by analogy, a primary concern of this research. In teaching, the connection is provided by the explicit use of a learning model to reason about the choice of teaching actions. In this learning paradigm, new concepts are incrementally refined and integrated into a body of expertise, rather than being evaluated against a static notion of correctness. The domain chosen for this experimentation is that of learning to solve "algebra story problems." A model of acquiring problem solving skills in this domain is described, including: representational structures for background knowledge, a problem solving architecture, learning mechanisms, and the role of analogies in applying existing problem solving abilities to novel problems. Examples of learning are given for representative instances of algebra story problems. After relating our views to the psychological literature, we outline the design of a teaching system. Finally, we insist on the interdependence of learning and teaching and on the synergistic effects of conducting both research efforts in parallel

Abstraction as a basis for the computational interpretation of creative cross-modal metaphor

Various approaches to computational metaphor interpretation are based on pre-existing similarities between source and target domains and/or are based on metaphors already observed to be prevalent in the language. This paper addresses similarity-creating cross-modal metaphoric expressions. It is shown how the “abstract concept as object” (or reification) metaphor plays a central role in a large class of metaphoric extensions. The described approach depends on the imposition of abstract ontological components, which represent source concepts, onto target concepts. The challenge of such a system is to represent both denotative and connotative components which are extensible, together with a framework of general domains between which such extensions can conceivably occur. An existing ontology of this kind, consistent with some mathematic concepts and widely held linguistic notions, is outlined. It is suggested that the use of such an abstract representation system is well adapted to the interpretation of both conventional and unconventional metaphor that is similarity-creating

Development and validation of computational models of cellular interaction

In this paper we take the view that computational models of biological systems should satisfy two conditions – they should be able to predict function at a systems biology level, and robust techniques of validation against biological models must be available. A modelling paradigm for developing a predictive computational model of cellular interaction is described, and methods of providing robust validation against biological models are explored, followed by a consideration of software issues

Connecting Levels of Analysis in Educational Neuroscience: A Review of Multi-level Structure of Educational Neuroscience with Concrete Examples

In its origins educational neuroscience has started as an endeavor to discuss implications of neuroscience studies for education. However, it is now on its way to become a transdisciplinary field, incorporating findings, theoretical frameworks and methodologies from education, and cognitive and brain sciences. Given the differences and diversity in the originating disciplines, it has been a challenge for educational neuroscience to integrate both theoretical and methodological perspective in education and neuroscience in a coherent way. We present a multi-level framework for educational neuroscience, which argues for integration of multiple levels of analysis, some originating in brain and cognitive sciences, others in education, as a roadmap for the future of educational neuroscience with concrete examples in moral education