  Hex is a complex game with a high branching factor. For the first time Hex is
being attempted to be solved without the use of game tree structures and
associated methods of pruning. We also are abstaining from any heuristic
information about Virtual Connections or Semi Virtual Connections which were
previously used in all previous known computer versions of the game. The
H-search algorithm which was the basis of finding such connections and had been
used with success in previous Hex playing agents has been forgone. Instead what
we use is reinforcement learning through self play and approximations through
neural networks to by pass the problem of high branching factor and maintaining
large tables for state-action evaluations. Our code is based primarily on
NeuroHex. The inspiration is drawn from the recent success of AlphaGo Zero.
