Learn More
There is a spectrum of methods for learning robot control. At one end there are model-free methods (eg. Q-learning, AHC, bucket brigade), and at the other there are model-based methods, (eg. dynamic programming by value or policy iteration). The advantage of one technique is the weakness of the other. Model-based methods use experience eeectively, but are(More)
We implement genetic algorithm based predictive model building as an alternative to the traditional stepwise regression. We then employ the Information Complexity Measure (ICOMP) as a measure of model fitness instead of the commonly used measure of R-square. Furthermore, we propose some modifications to the genetic algorithm to increase the overall(More)
a r t i c l e i n f o a b s t r a c t We introduce a new method for showing that the roots of the characteristic polynomial of certain finite lattices are all nonnegative integers. This method is based on the notion of a quotient of a poset which will be developed to explain this factorization. Our main theorem will give two simple conditions under which(More)
We introduce a new method for showing that the roots of the characteristic polynomial of a finite lattice are all nonnegative integers. Our method gives two simple conditions under which the characteristic polynomial factors. We will see that Stanley's Supersolvability Theorem is a corollary of this result. We can also use this method to demonstrate a new(More)
  • 1