What is the principle posited by Vladimir Vapnik in statistical learning theory, and how does it motivate the direct learning of policies in reinforcement learning?
Vladimir Vapnik, a prominent figure in the field of statistical learning theory, introduced a fundamental principle known as the Vapnik-Chervonenkis (VC) theory. This theory primarily addresses the problem of how to achieve good generalization from limited data samples. The core idea revolves around the concept of the VC dimension, which is a measure of the
How does the exploration-exploitation dilemma manifest in the multi-armed bandit problem, and what are the key challenges in balancing exploration and exploitation in more complex environments?
The exploration-exploitation dilemma is a fundamental challenge in the field of reinforcement learning (RL), particularly exemplified in the multi-armed bandit problem. This dilemma involves the decision-making process where an agent must choose between exploring new actions to discover their potential rewards (exploration) and exploiting known actions that have yielded high rewards in the past (exploitation).