Reinforcement Learning
(การเรียนรู้แบบเสริมกำลัง)
Definition
Reinforcement Learning (การเรียนรู้แบบเสริมกำลัง) Hard Skill
A machine learning paradigm where an agent learns to make decisions by taking actions in an environment to maximize cumulative rewards.
Expertise Level
Level 1
Basic
1. Understands fundamental concepts of reinforcement learning such as agents, environments, states, actions, and rewards.
2. Can implement simple RL algorithms like multi-armed bandit problems.
3. Familiar with basic terminology and theoretical foundations.
Level 2
Intermediate
1. Can implement and tune common RL algorithms like Q-learning and SARSA.
2. Understands exploration vs. exploitation trade-offs and policy evaluation.
3. Able to apply RL methods to moderate complexity environments or simulations.
Level 3
Advanced
1. Expertise in advanced RL algorithms including Deep Reinforcement Learning and Policy Gradient methods.
2. Can design and optimize RL models for complex real-world applications.
3. Able to analyze convergence, stability, and scalability of RL systems.
