Spinning Up is a deep reinforcement learning curriculum designed to teach the theory and implementation of deep reinforcement learning algorithms. It serves as a guided educational resource for understanding how agents interact with environments through mathematical models and code.
The project provides a research roadmap consisting of a curated collection of influential research papers and theoretical concepts. This literature study is designed to guide a deeper exploration of specific reinforcement learning domains.
The curriculum covers the implementation of reinforcement learning logic through standalone code examples and a study of core terminology and theoretical foundations.
