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Introduction

Learning Goals

  • Understand the Reinforcement Learning problem and how it differs from Supervised Learning

Summary

  • Reinforcement Learning (RL) is concerned with goal-directed learning and decision-making.
  • In RL an agent learns from experiences it gains by interacting with the environment. In Supervised Learning we cannot affect the environment.
  • In RL rewards are often delayed in time and the agent tries to maximize a long-term goal. For example, one may need to make seemingly suboptimal moves to reach a winning position in a game.
  • An agent interacts with the environment via states, actions and rewards.

Lectures & Readings

Required:

Optional:

N/A

Exercises