Algorithms for Reinforcement Learning (Synthesis Lectures on Artificial Intelligence and Machine Learning)
Algorithms for Reinforcement Learning (Synthesis Lectures on Artificial Intelligence and Machine Learning) READ MORE Algorithms for Reinforcement Learning (Synthesis Lectures on Artificial Intelligence and Machine Learning) Reinforcement learning is a learning paradigm concerned with learning to control a system so as to maximize a numerical performance measure that expresses a long-term objective. What distinguishes reinforcement learning from supervised learning is that only partial feedback is given to the learner about the learner's predictions. Further, the predictions may have long term effects through influencing the future state of the controlled system. Thus, time plays a special role. The goal in reinforcement learning is to develop efficient learning algorithms, as well as to understand the algorithms' merits and limitations. Reinforcement learning is of great interest because of the large number of practical applications that it can be used to address, ranging fro