What is David Silver's central idea in reinforcement learning?
My central focus in reinforcement learning revolves around creating agents that can learn optimal strategies through trial and error. This involves defining an environment, an agent's actions, and a reward signal. The goal is to develop algorithms that allow the agent to maximize its cumulative reward over time, often by balancing exploration of new actions with exploitation of known good actions.
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