Open Access Repositories: Recent submissions
Now showing items 2061-2080 of 4204
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Extending 2-D Smoothed Local Symmetries to 3-D
(MIT Artificial Intelligence Laboratory, 1985-11)3-D Smoothed Local Symmetries (3-D SLS's) are presented as a representation for three-dimensional shapes. 3-D SLS's make explicit the perceptually salient features of 3-D objects and are especially suited to representing ...
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A Program Design Assistant
(MIT Artificial Intelligence Laboratory, 1989-06)The DA will be a design assistant which can assist the programmer in low-level design. The input language of the DA is a cliché-based program description language that allows the specification and high-level design of ...
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Principles of Knowledge Representation and Reasoning in the FRAPPE System
(MIT Artificial Intelligence Laboratory, 1989-05)The purpose of this paper is to elucidate the following four important architectural principles of knowledge representation and reasoning with the example of an implemented system: limited reasoning, truth maintenance, ...
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Decision Representation Language (DRL) and Its Support Environment
(MIT Artificial Intelligence Laboratory, 1989-08)In this report, I describe a language, called Decision Representation Language (DRL), for representing the qualitative aspects of decision making processes such as the alternatives being evaluated, goals to satisfy, and ...
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Don't Loop, Iterate
(MIT Artificial Intelligence Laboratory, 1990-05)I describe an iteration macro for Common Lisp that is clear, efficient, extensible, and in excellent taste.
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The GSL Cookbook
(MIT Artificial Intelligence Laboratory, 1989-03)This cookbook contains recipes prepared for the GSL (Graduate Student Lunch) at the Massachusetts Institute of Technology Artificial Intelligence Laboratory.
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Determining the Limits of Automated Program Recognition
(MIT Artificial Intelligence Laboratory, 1989-06)Program recognition is a program understanding technique in which stereotypic computational structures are identified in a program. From this identification and the known relationships between the structures, a hierarchical ...
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Integrating vision modules with coupled MRFs
(MIT Artificial Intelligence Laboratory, 1985-12)I outline a project for integrating several early visual modalities based on coupled Markov Random Fields models of the physical processes underlying image formation, such as depth, albedo and orientation of surfaces. The ...
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Construction and Refinement of Justified Causal Models Through Variable-Level Explanation and Perception, and Experimenting
(MIT Artificial Intelligence Laboratory, 1985-12)The competence being investigated is causal modelling, whereby the behavior of a physical system is understood through the creation of an explanation or description of the underlying causal relations. After developing a ...
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Further Evidence Against the Recovery Theory of Vision
(MIT Artificial Intelligence Laboratory, 1989-02)The problem of three-dimensional vision is generally formulated as the problem of recovering the three-dimensional scene that caused the image. We have previously presented a certain line-drawing and shown that it has the ...
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Transcendence, Facticity, and Modes of Non-Being
(MIT Artificial Intelligence Laboratory, 1986-03)Research in artificial intelligence has yet to satisfactorily address the primordial fissure between human consciousness and the material order. How is this split reconciled in terms of human reality? By what duality is ...
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Vision Utilities
(MIT Artificial Intelligence Laboratory, 1985-12)This paper documents a collection of Lisp utilities which I have written while doing vision programming on a Symbolics Lisp machine. Many of these functions are useful both as interactive commands invoked from the Lisp ...
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A Counterexample to the Theory that Vision Recovers Three-Dimensional Scenes
(MIT Artificial Intelligence Laboratory, 1988-11)The problem of three-dimensional vision is generally formulated as the problem of recovering the three-dimensional scene that caused the image. Here we present a certain line-drawing and show that it has the following ...
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Test Programming by Program Composition and Symbolic Simulation
(MIT Artificial Intelligence Laboratory, 1985-11)Classical test generation techniques rely on search through gate-level circuit descriptions, which results in long runtimes. In some instances, classical techniques cannot be used because they would take longer than the ...
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Automated Program Recognition: A Proposal
(MIT Artificial Intelligence Laboratory, 1985-12)The key to understanding a program is recognizing familiar algorithmic fragments and data structures in it. Automating this recognition process will make it easier to perform many tasks which require program understanding, ...
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How to do Research At the MIT AI Lab
(MIT Artificial Intelligence Laboratory, 1988-10)This document presumptuously purports to explain how to do research. We give heuristics that may be useful in pickup up specific skills needed for research (reading, writing, programming) and for understanding and enjoying ...
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Jordan Form of (i+j over j) over Z[subscript p]
(MIT Artificial Intelligence Laboratory, 1985-07)The Jordan Form over field Z[subscript p] of J[superscript p][subscript p]n is diagonal for p > 3 with characteristic polynomial, ϕ(x) = x[superscript 3] - 1, for p prime, n natural number. These matrices have dimension ...
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IDEME: A DBMS of Methods
(MIT Artificial Intelligence Laboratory, 1985-08)In this paper, an intelligent database management system (DBMS) called IDEME is presented. IDEME is a program that takes as input a task specification and finds a set of methods potentially relevant to solving that task. ...
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Writing and Representation
(MIT Artificial Intelligence Laboratory, 1988-09)This paper collects several notes I've written over the last year in an attempt to work through my dissatisfactions with the ideas about representation I was taught in school. Among these ideas are the notion of a 'world ...
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Toward a Principle-Based Translator
(MIT Artificial Intelligence Laboratory, 1985-06)A principle-based computational model of natural language translation consists of two components: (1) a module which makes use of a set of principles and parameters to transform the source language into an annotated surface ...
