AI Terminology
Welcome to the AI Terminology section of the AI blog! This comprehensive glossary is designed to help you navigate the complex world of artificial intelligence. Here, you’ll find clear, concise definitions and explanations of key terms and concepts in AI, from foundational ideas like machine learning and neural networks to advanced topics such as reinforcement learning and variational autoencoders. Whether you’re a beginner or an expert, this resource is tailored to enhance your understanding and keep you updated with the latest advancements in the field.
Deep Reinforcement Learning
Dive into Deep Reinforcement Learning: Understand how AI learns from mistakes to improve decisions in complex environments. Perfect for tech enthusiasts and professionals.
Machine Learning • ML
Machine learning is a subset of artificial intelligence (AI) that enables computers to learn from experience and improve over time.
Reinforcement Learning • RL
Reinforcement learning is a subfield of machine learning, concerned with how software agents can learn to behave in complex, uncertain environments. It relies on feedback from the environment in order to improve the agent's behavior.
Action Model Learning
Action model learning is a subfield of machine learning that focuses on learning how to perform actions in the world.
Note: The above list of AI terms is sorted by the last update time.
AI Terminology Graph (interactive)
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