Title of the first RL Talk Series: Reinforcement Learning Unboxed: How Machines Learn to Act

Abstract:
Reinforcement Learning (RL) is a powerful paradigm that enables machines to learn optimal behaviors through interaction with their environments. In this first session of the IEEE Computer Society Türkiye Chapter’s introductory series on RL, we will present the foundational concepts underlying this field. The talk will describe what an RL agent is, how it perceives its surroundings, and how it gradually improves its decisions over time by receiving feedback in the form of rewards and penalties.

This session aims to provide a clear and accessible introduction to reinforcement learning as it applies to robotics, intelligent systems, and gaming. No prior experience is required—only curiosity and an interest in understanding how machines can learn to act autonomously by trial and error.

Speaker Bio:
Emir Arditi is a Ph.D. Candidate in Computer Engineering at Özyeğin University. His research focuses on Reinforcement Learning and Inverse Reinforcement Learning. He has been an active IEEE member for nine years, contributing in various leadership and organizational roles. His team has placed first in the IEEEXtreme Programming Competition three times and ranked among the Top 100 teams in IEEE Region 8 twice.

Event Details:

• Date: Wednesday, July 9th, 2025
• Time: 19:00 – 20:30 Türkiye Time
• Format: Online (The Zoom link will be provided after registration)
• Language: English

Registration:
Participation is free of charge. To reserve your spot, please register by clicking on IEEE Computer Society Türkiye Chapter Registration Form

About the Series:
This lecture marks the beginning of the Reinforcement Learning Talk Series organized by the IEEE Computer Society Türkiye Chapter. The series is designed to offer participants a solid foundation in RL concepts that will be further developed in subsequent sessions.