Computer Science and Artificial Intelligence Lab (CSAIL): Recent submissions

Now showing items 481-500 of 2625

  • Shadows and Cracks 

    Unknown author (MIT Artificial Intelligence Laboratory, 1971-06)
    The VIRGIN program will interpret pictures of crack and shadow free scenes by labelling them according to the Clowes/Huffman formalism. This paper indicates methods of extending the program to include cracks and shadows ...

  • Injection Molding at the MIT Artificial Intelligence Lab 

    Unknown author (MIT Artificial Intelligence Laboratory, 1995-02-23)
    This paper describes the injection molding equipment at the MIT Artificial Intelligence Lab and how to use it. Topic covered include mold design, insert molding, safety, and material properties.

  • Capture It, Name It, Own it: How to capture re-occurring patterns, name them and turn them into reusable functions via Emacs kbd-macros 

    Unknown author (MIT Artificial Intelligence Laboratory, 1992-05)
    The purpose of this talk is not to teach you about Emacs or Emacs kbd-macros, though we will use both as examples. I can teach you everything there is to know about Emacs and kbd-macros in 5 minutes. There are literally ...

  • Tomorrow's Surgery: Micromotors and Microrobots 

    Unknown author (MIT Artificial Intelligence Laboratory, 1992-07)
    Surgical procedures have changed radically over the last few years due to the arrival of new technology. What will technology bring us in the future? This paper examines a few of the forces whose timing are causing new ...

  • AI Lab Faculty 

    Unknown author (MIT Artificial Intelligence Laboratory, 1992-09)
    This document is meant to introduce new graduate students in the MIT AI Lab to the faculty members of the laboratory and their research interests. Each entry consists of the faculty member's picture, if available, some ...

  • A User's Guide to the AI Lab: Getting Started at Tech Square 

    Unknown author (MIT Artificial Intelligence Laboratory, 1991-08-18)

  • Fine Grained Robotics 

    Unknown author (MIT Artificial Intelligence Laboratory, 1991-02)
    Fine grained robotics is the idea of solving problems utilizing multitudes of very simple machines in place of one large complex entity. Organized in the proper way, simple machines and simple behaviors can lead to emergent ...

  • The Evolution of Society 

    Unknown author (MIT Artificial Intelligence Laboratory, 1991-08-05)
    We re-examine the evolutionary stability of the tit-for-tat (tft) strategy in the context of the iterated prisoner's dilemma, as introduced by Axelrod and Hamilton. This environment involves a mixture of populations of ...

  • Correction of Force Errors for Flexible Manipulators in Quasi-Static Conditions 

    Unknown author (MIT Artificial Intelligence Laboratory, 1990-12)
    This paper deals with the problem of controlling the interactions of flexible manipulators with their environment. For executing a force control task, a manipulator with intrinsic (mechanical) compliance has some advantages ...

  • An Experiment in Knowledge Acquisition for Software Requirements 

    Unknown author (MIT Artificial Intelligence Laboratory, 1990-05)
    The Requirements Apprentice (RA) is a demonstration system that assists a human analyst in the requirements-acquisition phase of the software-development process. By applying the RA to another example it has been possible ...

  • Extending 2-D Smoothed Local Symmetries to 3-D 

    Unknown author (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 ...

  • A Program Design Assistant 

    Unknown author (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 ...

  • Principles of Knowledge Representation and Reasoning in the FRAPPE System 

    Unknown author (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, ...

  • Decision Representation Language (DRL) and Its Support Environment 

    Unknown author (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 ...

  • Don't Loop, Iterate 

    Unknown author (MIT Artificial Intelligence Laboratory, 1990-05)
    I describe an iteration macro for Common Lisp that is clear, efficient, extensible, and in excellent taste.

  • The GSL Cookbook 

    Unknown author (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.

  • Determining the Limits of Automated Program Recognition 

    Unknown author (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 ...

  • Integrating vision modules with coupled MRFs 

    Unknown author (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 ...

  • Construction and Refinement of Justified Causal Models Through Variable-Level Explanation and Perception, and Experimenting 

    Unknown author (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 ...

  • Further Evidence Against the Recovery Theory of Vision 

    Unknown author (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 ...