What is Reinforcement Learning Exploration-Exploitation Tradeoff?
The Exploration-Exploitation Tradeoff in
Reinforcement Learning refers to the dilemma of choosing between exploring new actions or exploiting the actions that have yielded high rewards in the past. Exploration allows the agent to discover potentially better actions, while exploitation focuses on exploiting the known good actions to maximize immediate rewards. Striking the right balance between exploration and exploitation is crucial for an agent to learn and improve its performance over time.
