Reinforcement Learning Algorithms with Python

Dueling DQN

In the paper Dueling Network Architectures for Deep Reinforcement Learning (https://arxiv.org/abs/1511.06581), a novel neural network architecture with two separate estimators was proposed: one for the state value function and the other for the state-action advantage value function.

The advantage function is used everywhere in RL and is defined as follows:

The advantage function tells us the improvement of an action, , compared to the average action in a given state, . Thus, if is a positive value, this means that the action, ...