Learning Strategies or Paradigms refer to the higher-level strategies that an AI model can use to enhance its learning process, often regardless of the learning type being used. This category includes: Transfer Learning, Multi-task Learning, Active Learning and Semi-Supervised Learning.
In reinforcement learning, AI systems learn by interacting with their environment and receiving feedback in the form of rewards or penalties. The AI system aims to maximise the cumulative reward over time by choosing the optimal sequence of actions.
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