Exploration Vs Exploitation
Exploration vs Exploitation is a fundamental concept in data science and artificial intelligence that refers to the trade-off between trying out new options (exploration) and exploiting the best option found so far (exploitation). In other words, it is the dilemma between gathering more information and making the best decision based on the current information. This concept is particularly relevant in the context of reinforcement learning, where an agent interacts with an environment to learn the optimal policy. The agent must decide whether to explore new actions or exploit the current best action based on the information gathered so far. The optimal balance between exploration and exploitation depends on the problem at hand and can be influenced by factors such as the level of uncertainty in the environment and the cost of exploration.
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