Reinforcement Learning

Reinforcement Learning (RL) is a type of machine learning method that involves learning optimal behavioral strategies through the interaction between an agent and its environment, with the aim of maximizing cumulative rewards. Its core objective is to achieve autonomous decision optimization in dynamic environments, enhancing system performance. In complex tasks such as natural language processing, RL can effectively address sequential decision-making problems, improving the adaptability and robustness of models, and thus has broad application value.