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Reinforcement Learning
Learning through trial and error with rewards and penalties.
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Key Reinforcement Learning concepts
A specific task or decision made by an AI system
Bellman equationA mathematical equation used in dynamic programming to find the optimal solution to a problem by breaking it down into smaller subproblems
candidate samplingA technique used in machine learning to select a subset of examples from a large dataset for training
Deep Q-NetworkA type of artificial intelligence algorithm that learns to make decisions by trial and error
environmentThe external conditions and circumstances that affect the behavior and performance of a system or agent
episodeA single trial or attempt in a learning process
epsilon greedy policyA decision-making strategy that balances exploration and exploitation by choosing the best option most of the time, but occasionally selecting a random option
experience replayA technique used in reinforcement learning where an agent stores and reuses past experiences to improve its learning efficiency