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(Reinforcement Learning): In reinforcement learning, an agent is an entity that interacts with an environment and takes specific actions to achieve rewards. Using the concept of “trial and error” for reinforcement learning, the agent is the one that’s doing the trials and making the errors. For example, if a reinforcement learning system is trying to find a solution to a maze, the agent would be the specific actor that is trying to find the solution.