We think that more research into reinforcement learning principles in motor skill acquisition will improve our ability to make specific and personalised recommendations for practitioners. As research in this area grows, we expect to be able to make detailed prescriptions based on interactions of the individual, task, and environment. In the interim, however, there are some general recommendations that can made from burgeoning research in this area and decades of reinforcement learning studies in other domains. Reinforcement learning describes the process by which we adjust our behavior based on prediction errors in order to maximise rewards and minimise punishments. In this chapter, we offer empirical evidence and strong theoretical arguments to support the idea that this learning model is probably the most important for understanding skill acquisition. Reinforcement learning principles can be used to explain performance adaptation and long-term retention of motor skills and should, therefore, inform how instructors and practitioners design practice conditions. Specifically, instructors should attempt to maximise reward-prediction errors by increasing the reward associated with successful outcomes.
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