thesis on eval function learning in Arimaa

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jdart
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thesis on eval function learning in Arimaa

Post by jdart » Fri Dec 04, 2015 2:46 pm

http://arimaa.com/arimaa/papers/ThomasH ... Arimaa.pdf

Basically this used supervised learning against a database of strong server games (something like the MMTO method used in Shogi). The eval function is modelled as a linear or quadradic function. But even in the linear case it appears that the weights ultimately control a polynomal function (not sure I am understanding that on a quick read).

The author used either a linear programming solver (Mosek) or a quadratic programming solver (Gurobi) to do the optimization. These are expensive commercial solvers (but free for academic use).

--Jon

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