A specialized ATMS for efficiently computing equivalence relations in multiple contexts is introduced. This specialized ATMS overcomes the problems with existing solutions to reasoning with equivalence relations. The most direct implementation of an equivalence relation in the ATMS-encoding the reflexive, transitive, and symmetric rules in the consumer architecture-produces redundant equality...
The task of inductive learning from examples places constraints on the representation of training instances and concepts. These constraints are different from, and often incompatible with, the constraints placed on the representation by the performance task. This incompatibility is severe when learning functional concepts and explains why previous researchers have...
AM is a computer program written by Doug Lenat that discovers elementary
mathematics starting from some initial knowledge of set theory. The success of this
program is not clearly understood.
This work is an attempt to explore the search space of AM in order to understand the success and eventual...
A forward-chaining logic programming system (FORLOG) has been developed at Oregon State University. This system coupled with an assumption-based truth maintenance system (ATMS), provides an alternative to the logic programming paradigm of backward-chaining with Horn clauses. To compare FORLOG to this paradigm, we define a subset of FORLOG, called mini-FORLOG,...
A key aspect of how we understand the world revolves around an ability to manipulate our surroundings to experiment. From the scientific method through theories of child development, the ability to experiment is deemed critical; however, few studies have been performed to understand the strengths and weaknesses of different experimental...
Generalized Radial Basis Functions were used to construct networks
that learn input-output mappings from given data. They are
developed out of a theoretical framework for approximation based
on regularization techniques and represent a class of three-layer
networks similar to backpropagation networks with one hidden
layer.
A network using Gaussian base...
This thesis compares two methods for studying the problem-solving processes of
mechanical design engineers. The first method, verbal protocol analysis, was applied
by L. Stauffer to construct a problem-solving model of mechanical design. The
second method, timing analysis, measures the time intervals separating drawing or
speaking actions during the design...
Many important application problems in engineering can be formalized as nonlinear
optimization tasks. However, numerical methods for solving such problems
are brittle and do not scale well. For example, these methods depend critically
on choosing a good starting point from which to perform the optimization search.
In high-dimensional spaces, numerical...
Knowledge compilation improves search-intensive problem-solvers that are easily specified but inefficient. One promising approach improves efficiency by constructing a database of problem-instance/best-action pairs that replace problem-solving search with efficient lookup. The database is constructed by reverse enumeration- expanding the complete search space backwards, from the terminal problem instances. This approach...
The goal of Inductive Learning is to produce general rules from a set of seen examples, which can then be applied to other unseen examples. ID3 is an inductive learning algorithm that can be used for the classification task. The input to the algorithm is a set of tuples of...