We describe and evaluate a system for learning domainspecific control knowledge. In particular, given a planning domain, the goal is to output a control policy that performs well ...
Nowadays, people start to accept fuzzy rule–based systems as flexible and convenient tools to solve a myriad of ill–defined but otherwise (for humans) straightforward tasks s...
Abstract— Q-learning is a technique used to compute an optimal policy for a controlled Markov chain based on observations of the system controlled using a non-optimal policy. It ...
This paper is concerned with reachable set computation for non-linear systems using hybridization. The essence of hybridization is to approximate a non-linear vector field by a s...
We consider linear systems arising from the use of the finite element method for solving a certain class of linear elliptic problems. Our main result is that these linear systems, ...
Erik G. Boman, Bruce Hendrickson, Stephen A. Vavas...