The general tool: residual networks variant of convolutional NNs, MCTS-like variable-depth tree search. Prerequisites: input can be presented as K layers of N-D data (where N=1,2,3… not too large), the action space is discrete. If the actions are not discrete, an additional small module would be needed to quantize the action space based on the neural network’s action priors.
The general tool: residual networks variant of convolutional NNs, MCTS-like variable-depth tree search. Prerequisites: input can be presented as K layers of N-D data (where N=1,2,3… not too large), the action space is discrete. If the actions are not discrete, an additional small module would be needed to quantize the action space based on the neural network’s action priors.