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Computational Imagery
Author(s) -
Glasgow Janice,
Papadias Dimitri
Publication year - 1992
Publication title -
cognitive science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.498
H-Index - 114
eISSN - 1551-6709
pISSN - 0364-0213
DOI - 10.1207/s15516709cog1603_2
Subject(s) - mental image , computer science , mental representation , representation (politics) , cognition , set (abstract data type) , cognitive science , cognitive psychology , scheme (mathematics) , working memory , term (time) , artificial intelligence , psychology , mathematics , mathematical analysis , neuroscience , politics , political science , law , programming language , physics , quantum mechanics
After many years of neglect, the topic of mental imagery has recently emerged as an active area of research and debate in the cognitive science community. This article proposes a concept of computational imagery, which has potential applications to problems whose solutions by humans involve the use of mental imagery. Computational imagery can be defined as the ability to represent, retrieve, and reason about spatial and visual information not explicitly stored in long‐term memory. The article proposes a knowledge representation scheme for computational imagery that incorporates three representations: a long‐term memory, descriptive representation and two working‐memory representations, corresponding to the distinct visual and spatial components of mental imagery. The three representations, and a set of primitive functions, are specified using a formal theory of arrays and implemented in the array‐based language Nial. Although results of studies in mental imagery provide initial motivation for the representations and functionality of the scheme, our ultimate concerns are expressive power, inferential adequacy, and efficiency.