devakar771/Season-of-code
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game2048_engine: The core engine of the game that allows the user or a model to interact with the game. model: The architecture of the neural network is defined using keras. Game2048: The GUI for the game will allows the user to see the outcomes using graphical elements. Implemented using tkinter. For learning the Q-values a convolution network was used. Can be viewed from "Architecture.png". Constants used: # board_size = 4 # gamma for Q-learning: 0.9 # capacity of memory after which the the saved experiences are used to train the NN: 6144 # batch size of the saved experiences used training: 512 # coefficient of reward given for getting max value: 0.1 # initial learning rate: 0.001 --> exponential decay # initial epsilon for epsilon greedy approach: 0.9 --> epsilon /= 1.005 after episodes > 20000 # if random number < epsilon then a move is sampled from the q-values output from the NN not by assuming a uniform distribution but instead the output was sent to a softmax layer to extract the probabilties and then sample a move considering the probabilities. # Loss function: Meaen squared error # Optimizer: RMS prop # Final trainied weights: bestWt.zip
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