News

• This page is still under construction...

Research

• Working paper on part-whole relations (135 kB PostScript)
  ABSTRACT: Part-whole relations appear throughout human knowledge. Their ubiquity suggests that they play an important role in intelligence. We conjecture that the cognitive value of partonomic knowledge lies in its ability to support translation between representations at different levels of granularity. This permits more effective problem solving by allowing reasoners to integrate the unique benefits that different representations can offer.

We describe a representation for part-whole relations that supports this perspective. Our representation captures two types of partonomic knowledge: decompositions and knowledge translations. Decompositions identify the parts that compose objects. Knowledge translations relate knowledge about objects to knowledge about their parts. Our approach organizes partonomic knowledge around a taxonomy of decomposition functions. This allows us to use inheritance to share partonomic knowledge among similar decompositions.

• Master's Thesis: Automated Reasoning About Classical Mechanics (592 kB PostScript)
  (aka MIT-AI-TR-1422)
  ABSTRACT: In recent years, researchers in artificial intelligence have become interested in replicating human physical reasoning talents in computers. One of the most important skills in this area is predicting how physical systems will behave. This thesis discusses an implemented program that generates algebraic descriptions of how systems of rigid bodies evolve over time. Discussion about the design of this program identifies a physical reasoning paradigm and knowledge representation approach based on mathematical model construction and algebraic reasoning. This paradigm offers several advantages over methods that have become popular in the field, and seems promising for reasoning about a wide variety of classical mechanics problems.

My Picture Gallery

Fun

• Stanford Running Club
• Stanford Canadian Club
• My brother Pete's home page
• My former employer: Ascent Technology
• My bachelor's and master's degrees: MIT AI Lab
• My high school: University of Toronto Schools
• My elementary school: Toronto Montessori Schools

Contact Info

Robotics Laboratory
Gates Building 1A, Room 128
Computer Science Department
Stanford University
Stanford, CA 94305-9010

(415) 725-8787 [office]
(415) 497-6966 [home]

Email: leon@cs.stanford.edu

This page last updated: May 4, 1997