Therefore we incorporate them as separate features in the model, and allow the learning process to estimate their weights.
we select actions a based on the current state s and the partial environment model q, resulting in the following policy definition: φ(s,a ,q) , where the feature representation φ(s, a, q) has been extended to be a function of q.