def __init__(self): self.size = 50000 self.minibatch_size = 128 self.n_net = neuralnet(self.minibatch_size) self.memory = memory(size=self.size) self.ale = ale(self.memory, frames_to_skip=6) # 5 for space invaders # Loading model self.n_net.loadModel('./models/Improved_Breakout_AS.model.weights.NN.NMem.3707295')
def __init__(self): self.size = 50000 self.minibatch_size = 128 self.n_net = neuralnet(self.minibatch_size) self.memory = memory(size=self.size) self.ale = ale(self.memory, frames_to_skip=6) # 5 for space invaders # Loading model self.n_net.loadModel( './models/Improved_Breakout_AS.model.weights.NN.NMem.3707295')
def __init__(self): self.size = 100000 # memory size ~ 5Gb self.epsilon_step_dec = 700000 # Counter for epsilon dec. step self.M = 0 # Episodes self.T = 0 # Sequence max length self.minibatch_size = 128 # Minibatch size self.steps = 0 # Steps counter, inc. only self.count = 0 # Saving counter self.actions_number = 4 # Left, right, up, nothing self.n_net = neuralnet(self.minibatch_size) self.memory = memory(size=self.size) self.ale = ale(self.memory, frames_to_skip=6) # 4 in paper (5 for space invaders)
def __init__(self): self.size = 50000 self.minibatch_size = 128 self.n_net = neuralnet(self.minibatch_size) self.memory = memory(size=self.size) self.ale = ale(self.memory, frames_to_skip=6) # 5 for space invaders