Is the temperature equal to epsilon in Reinforcement Learning?

This is a piece of code from my homework. # action policy: implements epsilon greedy and softmax def select_action(self, state, epsilon): qval = self.qtable[state] prob = [] if (self.softmax): # use Softmax distribution prob = sp.softmax(qval / epsilon) #print(prob) else: # assign equal value to all actions prob = np.ones(self.actions) * epsilon / (self.actions -1)…

What is the difference between the concepts “known environment” and “deterministic environment”?

According to the book “Artificial Intelligence: A Modern Approach”, “In a known environment, the outcomes (or outcome probabilities if the environment is stochastic) for all actions are given.”, and in a deterministic environment, “the next state of the environment is completely determined by the current state and the action executed by the agent…”. What’s the…

Is it possible to train a neural network with 3 inputs and 12 outputs?

The selection of experimental data includes a set of vectors of different dimensions. The input is a 3-dimensional vector, and the output is a 12-dimensional vector. The sample size is 120 pairs of input 3-dimensional and output 12-dimensional vectors. Is it possible to train such a neural network (in MATLAB)? Which structure of the neural…

Efficient implementation of seperable convolution in tensorflow

It seems like the native implementation of separable convolution in tensorflow is not efficient. https://github.com/tensorflow/tensorflow/issues/12940 Is anyone aware how can we get an efficient implementation of separable convolution in tensorflow from somewhere? If not is there any working/efficient implementation of separable convolution in other libraries?