Reinforcement learning is a machine learning paradigm where an agent learns by taking actions in an environment and receiving rewards or penalties as feedback. Through repeated trial and error, the agent discovers strategies that maximize cumulative reward over time. Reinforcement learning has achieved superhuman performance in games like Go and Chess and drives advances in robotics, control systems, and autonomous decision-making.
Reinforcement Learning
Reinforcement learning is a machine learning paradigm where an agent learns by taking actions in an environment and receiving rewards or penalties as feedback. Through repeated trial and error, the agent discovers strategies that maximize cumulative reward over time. Reinforcement learning has achieved superhuman performance in games like Go and Chess and drives advances in robotics, control systems, and autonomous decision-making.