Finally, each vector is passed through a two-layer, fully connected network (decoder in Fig. ). The first layer has 128 neurons, and the second (output layer) has only one. A ReLu activation function is used after the first layer. After the second layer, every encoded vector now gets a single number as output. We take the value for each and use the softmax function to convert the list of values into probabilities -commonly used to model policies in RL .