Metaphor And Artificial Intelligence

This special issue arose out of a symposium on metaphor and artificial intelligence in which the main orientation was computational models and psychological processing models of metaphorical understanding. The papers in this issue discuss: *implemented computational systems for handling different aspects of metaphor understanding; *how metaphor can be accommodated in accepted logical representational frameworks; *psychological processes involved in metaphor understanding; and *the cross-linguistic cognitive reality of conceptual metaphors.

This special issue arose out of a symposium on metaphor and artificial intelligence in which the main orientation was computational models and psychological processing models of metaphorical understanding. The papers in this issue discuss: *implemented computational systems for handling different aspects of metaphor understanding; *how metaphor can be accommodated in accepted logical representational frameworks; *psychological processes involved in metaphor understanding; and *the cross-linguistic cognitive reality of conceptual metaphors.

Mind, Machine, and Metaphor is a rich, original, and wide-ranging view of legal theory in the context of artificial intelligence (AI) research. It is essential reading for legal theorists and for legal scholars and students of AI with an interest in each other's fields.

How the moves of thirty-two chess pieces over sixty-four squares can help us understand the workings of the mind. When we play the ancient and noble game of chess, we grapple with ideas about honesty, deceitfulness, bravery, fear, aggression, beauty, and creativity, which echo (or allow us to depart from) the attitudes we take in our daily lives. Chess is an activity in which we deploy almost all our available cognitive resources; therefore, it makes an ideal laboratory for investigation into the workings of the mind. Indeed, research into artificial intelligence (AI) has used chess as a model for intelligent behavior since the 1950s. In Chess Metaphors, Diego Rasskin-Gutman explores fundamental questions about memory, thought, emotion, consciousness, and other cognitive processes through the game of chess, using the moves of thirty-two pieces over sixty-four squares to map the structural and functional organization of the brain. Rasskin-Gutman focuses on the cognitive task of problem solving, exploring it from the perspectives of both biology and AI. Examining AI researchers' efforts to program a computer that could beat a flesh-and-blood grandmaster (and win a world chess championship), he finds that the results fall short when compared to the truly creative nature of the human mind.

This volume brings together the work of researchers from various disciplines where aspects of descriptive, mathematical, computational or design knowledge concerning metaphor and analogy, especially in the context of agents, have emerged. The book originates from an international workshop on Computation for Metaphors, Analogy, and Agents (CMAA), held in Aizu, Japan in April 1998. The 19 carefully reviewed and revised papers presented together with an introduction by the volume editor are organized into sections on Metaphor and Blending, Embodiment, Interaction, Imitation, Situated Mapping in Space and Time, Algebraic Engineering: Respecting Structure, and a Sea-Change in Viewpoints.

Mind, Machine, and Metaphor is a rich, original, and wide-ranging view of legal theory in the context of artificial intelligence (AI) research. It is essential reading for legal theorists and for legal scholars and students of AI with an interest in each other's fields.

This series will include monographs and collections of studies devoted to the investigation and exploration of knowledge, information, and data processing systems of all kinds, no matter whether human, (other) animal, or machine. Its scope is intended to span the full range of interests from classical problems in the philosophy of mind and philosophical psychol ogy through issues in cognitive psychology and sociobiology (concerning the mental capabilities of other species) to ideas related to artificial intelligence and computer science. While primary emphasis will be placed upon theoretical, conceptual, and epistemological aspects of these problems and domains, empirical, experimental, and methodological studies will also appear from time to time. The problems posed by metaphor and analogy are among the most challenging that confront the field of knowledge representation. In this study, Eileen Way has drawn upon the combined resources of philosophy, psychology, and computer science in developing a systematic and illuminating theoretical framework for understanding metaphors and analogies. While her work provides solutions to difficult problems of knowledge representation, it goes much further by investigating some of the most important philosophical assumptions that prevail within artificial intelligence today. By exposing the limitations inherent in the assumption that languages are both literal and truth-functional, she has advanced our grasp of the nature of language itself. J.R.F.