Brick Tic-Tac-Toe: Exploring the Generalizability of AlphaZero to Novel Test Environments. (arXiv:2207.05991v1 [cs.LG])

Traditional reinforcement learning (RL) environments typically are the same
for both the training and testing phases. Hence, current RL methods are largely
not generalizable to a test environment which is conceptually similar but
different from what the method has been trained on, which we term the novel
test environment. As an effort to push RL research towards algorithms which can
generalize to novel test environments, we introduce the Brick Tic-Tac-Toe
(BTTT) test bed, where the brick position in the test …

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