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Currently, the implementation of DeepMinimax returns the best depth1 guess associated with worst depth 2 outcome. However, this will not work for depths of 3+. Suppose that at depth 3+, the solver realises it is essential to return some guess, Guess A, at depth 2 in order to avoid major problems. The depth 1 solver would have no idea that it needs to play Guess A because the knowledge learnt at depth three is not being conveyed back up the chain.
Deep entropy doesn't have this problem because it modifies the guess. This is probably an acceptable workaround although an alternative is that deep guesses have a list (of length n) corresponding to the worst outcome at each depth n.
The text was updated successfully, but these errors were encountered:
Currently, the implementation of DeepMinimax returns the best
depth1
guess associated with worstdepth 2
outcome. However, this will not work for depths of 3+. Suppose that at depth 3+, the solver realises it is essential to return some guess, Guess A, at depth 2 in order to avoid major problems. The depth 1 solver would have no idea that it needs to play Guess A because the knowledge learnt at depth three is not being conveyed back up the chain.Deep entropy doesn't have this problem because it modifies the guess. This is probably an acceptable workaround although an alternative is that deep guesses have a list (of length n) corresponding to the worst outcome at each depth n.
The text was updated successfully, but these errors were encountered: