Reinforcement Learning Algorithms with Python

Implementation

The implementation of ESBAS is easy, as it involves the addition of only a few components. The most substantial part is in the definition and the optimization of the off-policy algorithms of the portfolio. Regarding these, ESBAS does not bind the choice of the algorithms. In the paper, both Q-learning and DQN are used. We have decided to use DQN, so as to provide an algorithm that is capable of dealing with more complex tasks that can be used with environments with the RGB state space. We went through DQN in great detail in Chapter 5, Deep Q-Network, and for ESBAS, we'll use the same implementation.

The last thing that we need to specify before going through the implementation is the portfolio's composition. We created a diversified ...