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What is Reinforcement Learning?

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Reinforcement Learning is a branch of AI that focuses on training agents to make decisions through trial and error in a specific environment. By employing positive reinforcement and punishments, businesses can teach machines to optimise actions and learn from rewards, enabling autonomous decision-making in dynamic situations.

Other Definitions

Instance-Based Learning

Instance-Based Learning is an AI approach where models make predictions based on similarity to previously seen examples. Instead of generalising from a predefined set…

Artificial General Intelligence (AGI)

Artificial General Intelligence refers to AI systems capable of understanding, learning, and performing any intellectual task as humans do. Although AGI remains aspirational, it…

Transfer Learning

Transfer Learning is a technique that allows AI models to apply knowledge gained from one task to another related task. By leveraging pre-trained models…

Distributed Computing

istributed Computing refers to the use of multiple computers or servers to perform computational tasks in a networked environment. It enables businesses to process…
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