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Welcome to the Reinforcement Learning (RL) Track of CSOC'26 — we're excited to have you on board!

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Introduction

What Is Reinforcement Learning?

Reinforcement Learning (RL) is a foundational branch of machine learning in which an autonomous agent learns to make sequential decisions by interacting with an environment. Rather than learning from a static dataset, the agent continuously takes actions, observes the consequences, and receives feedback in the form of rewards or penalties. Over time, the agent refines its behavior to maximize its cumulative reward — developing strategies that go far beyond simple pattern recognition.

RL has powered some of the most remarkable achievements in modern AI, from mastering complex games like Chess and Go to optimizing real-world systems in robotics, healthcare, and autonomous driving.

What You'll Learn

In Level 1, we will lay a solid mathematical and conceptual foundation for Reinforcement Learning. The focus will be on understanding how agents learn through interaction and how to formally represent decision-making problems.

Topics covered include:

• Multi-Armed Bandits
  • The Exploration vs. Exploitation dilemma
  • Greedy and ε-greedy action-selection strategies
  • Action-value estimation methods
  • Regret minimization and optimal decision-making
• Markov Decision Processes (MDPs)
  • States, actions, rewards, and transition dynamics
  • The Markov property and why it matters
  • Episodic vs. continuing tasks
  • Policies, value functions, and the Bellman equations
  • Modeling real-world problems as MDPs

By the end of this level, you will have a rigorous understanding of the mathematical framework underlying Reinforcement Learning and will be able to formally model and analyze simple decision-making problems.

Communities

All announcements, resources, and updates will be disseminated through the CSOC Website and the official Discord Community. Please ensure you have registered on the website and joined the Discord server to stay informed.

If you do not receive a timely response on Discord, feel free to reach out directly via WhatsApp:

• Rudranil Jadhav — 9096290279
• Sebastian — 9967215737