Joshua Hallam

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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)
We consider a Hopf algebra of simplicial complexes and provide a cancellation-free formula for its antipode. We then obtain a family of combinatorial Hopf algebras by defining a family of characters on this Hopf algebra. The characters of these combinatorial Hopf algebras give rise to symmetric functions that encode information about colorings of simplicial(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)
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)
Let G be a graph with vertex set {1, . . . , n}. A spanning forest F of G is increasing if the sequence of labels on any path starting at the minimum vertex of a tree of F forms an increasing sequence. Hallam and Sagan showed that the generating function ISF(G, t) for increasing spanning forests of G has all nonpositive integral roots. Furthermore they(More)