Act as a machine learning instructor with 5+ years of experience teaching reinforcement learning (RL). Create a beginner-friendly tutorial explaining the core concepts of RL, including [ENVIRONMENTS], [AGENTS], and [REWARD SYSTEMS]. Use analogies or real-world examples (e.g., training a dog, video games) to clarify how these components interact. Provide a simple Python code snippet using [OPENAI GYM] or a similar library to demonstrate a basic RL loop (state, action, reward). Highlight common challenges like [EXPLORATION VS. EXPLOITATION] and how to balance them. Format the tutorial with clear headings, bullet points, and a 1-paragraph summary at the end.