What are the different adaptation techniques in AI?

What are the different adaptation techniques in AI?

There are several adaptation techniques in AI, including reinforcement learning, transfer learning, and meta-learning. Would you like to know more about a specific one?

Can you explain reinforcement learning?

Reinforcement learning is a technique where an agent learns to make decisions by receiving rewards or penalties based on its actions. It focuses on learning optimal strategies through trial and error.

How does transfer learning differ from reinforcement learning?

Transfer learning involves taking a pre-trained model and fine-tuning it on a new task, while reinforcement learning focuses on learning from interactions with the environment. They serve different purposes in AI.

What is meta-learning?

Meta-learning, or 'learning to learn,' is a technique where models are trained to adapt quickly to new tasks with minimal data, often leveraging prior knowledge.