Reinforcement Learning Algorithms with Python

Choosing the appropriate algorithm

The main driving force that differentiates the various types of RL algorithms is sample efficiency and training time.

We consider sample efficiency as the number of interactions with the environment that an agent has to make in order to learn the task. The numbers that we'll provide are an indication of the efficiency of the algorithm and are measured with respect to other algorithms on typical environments.

Clearly, there are other parameters that influence this choice, but usually, they have a minor impact and are of less importance. Just to give you an idea, the other parameters to be evaluated are the availability of CPUs and GPUs, the type of reward function, the scalability, and the complexity of the ...