Abstract: Systems and methods for enhanced document analysis and identification through a reinforcement learning framework are provided. A system may employ computer based reinforcement learning to interact with large populations of documents to help users achieve a goal. To accomplish this goal, rewards, value functions, states, policies, and actions may be modeled and various tools within the system can be used to achieve the user's goal. As actions are performed, the results of these actions may be used to update state, assess rewards, and update value functions and policy functions. If the goal is not achieved, the system may make adjustments by adjusting policies, pushing the user closer to their goal by methods of reinforcement learning. Once the goal is achieved, such as a confidence that at least a certain percentage of relevant documents have been identified, relevant documents may be provided to a party desiring the documents.