Python Reinforcement Learning Projects

Model

In the previous sections, we discussed how the environment is not fully known to the agent. In other words, the agent usually does not have an idea of how the internal algorithm of the environment looks. The agent thus needs to interact with it to gain information and learn how to maximize its expected cumulative reward. However, it is possible for the agent to have an internal replica, or a model, of the environment. The agent can use the model to predict how the environment would react to some action in a given state. A model of the stock market, for example, is tasked with predicting what the prices will look like in the future. If the model is accurate, the agent can then use its value function to assess how desirable future states ...