Reinforcement Learning with TensorFlow

The S state set

The S state set is a set of different states, represented as s, which constitute the environment. States are the feature representation of the data obtained from the environment. Thus, any input from the agent's sensors can play an important role in state formation. State spaces can be either discrete or continuous. The starts from start state and has to reach the goal state in the most optimized path without ending up in bad states (like the red colored state shown in the diagram below).

Consider the following gridworld as having 12 discrete states, where the green-colored grid is the goal state, red is the state to avoid, and black is a wall that you'll bounce back from if you hit it head on:

The states can be represented ...