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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)

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 main theorem gives two simple conditions under which the characteristic polynomial factors in this way. We will see that Stanley's Supersolvabil-ity Theorem is a corollary of this result. We can also use this method to… (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)

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)

- Joshua W. Hallam, Olcay Akman, Füsun Akman
- 2010

A Genetic Algorithm (GA) is an evolutionary computation technique inspired by the principle of biological evolution via natural selection. It employs the fundamental components of evolution, such as selection, mating, and mutation, which continue from generation to generation, creating better solutions as time progresses. Although it is mostly used as an… (More)

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