Reward Booster Reinforcement Learning is a reinforcement learning method that uses a reward booster to encourage the agent to explore and find better rewards. In this method, the reward function is augmented with a bonus term that is proportional to the difference between the current reward and the maximum reward found so far. This encourages the agent to seek out new and more rewarding states, as it gets a larger reward for finding a better reward than it has seen before.
