`markov-decision-process` Related Article Results

Deep Reinforcement Learning (DRL) is an artificial intelligence approach that combines the fundamental principles of reinforcement learning (RL) with the representational power of deep learning (DL). This method enables an agent to learn a policy through trial and error in an environment, with the goal of maximizing the total future rewards. DRL employs deep neural networks to perform this process in high-dimensional and complex state spaces. Historical Background The origins of reinforcement le