Reinforcement learning approaches often struggle to learn complex behaviors due to the exploration-exploitation dilemma. A novel approach called "Penalize with Slots" suggests a solution by introducing a penalty mechanism based on a set of slots. These slots represent important aspects of the agent's behavior, and the agent is penalized when its ac