Commonsense Reasoning for RL

The application of commonsense reasoning in reinforcement learning (RL) agents, referred to as Commonsense Reasoning for RL, involves endowing RL agents with reasoning capabilities based on human common sense. This enables them to make more rational and efficient decisions in complex and dynamic environments. The goal is to enhance the understanding and generalization abilities of RL agents by integrating commonsense knowledge bases and reasoning algorithms, thereby achieving better adaptability and robustness in practical application scenarios.