I present a new heuristic search approach to compute approximate answers for the probability query in belief nets. This approach can compute the 'best' bounds for a query in a period of any given time (if time permitted, it will get an exact value). It inherits the essence of Symbolic...
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 purpose of the present investigation was to develop an adaptive teaching model for an interactive computer-assisted instruction (CAT) program and to evaluate the effectiveness of the implementation of individualized examples or individualized
examples in personalized contexts. Translating word problems into equations provided the context for the CAT investigation. Four...
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...
We have developed SearchPak, a machine independent parallel searching tool on shared and distributed memory machines. It can be used for combinatorial optimization problems and OR-parallel computations as well. Both depth-first and best-first search of the state space can be performed using the SearchPak. With SearchPak, a user just provides...
High level data-parallel languages are easy to use and shield the programmer from machine specific details. A simple and efficient way of providing an interface to such languages is to develop a machine-independent compiler and a routing library, which isolates the low-level machine dependent communication functions, The compiler translates the...
In real-time control systems, the value of a control decision depends not
only on the correctness of the decision but also on the time when that decision
is available. Recent work in real-time decision making has used machine learning
techniques to automatically construct reactive controllers, that is, controllers
with little...
Reasoning about any realistic domain always involves a degree of uncertainty.
Probabilistic inference in belief networks is one effective way of reasoning under
uncertainty. Efficiency is critical in applying this technique, and many researchers
have been working on this topic. This thesis is the report of our research in this...
In this thesis, A nonlinear methodology for the control of the highly
maneuverable, high performance aircraft HARV (F-18) is studied by using sliding-mode
control (SMC). This control law, which takes a continuous function when the
input constraints are not considered, satisfies the reachability condition by which
concerned states are driven...
Dataparallel C has been designed for various kinds of architectures and was developed jointly at University of New Hampshire and Oregon State University.
This project dealt with porting the libraries to the nCUBE 2 system and helping a user compile his programs on nCUBE 2 directly from a Sun workstation...