Technical Workshop " Unveiling the Potential of Deep Reinforcement Learning (DRL): Methods and Applications" By: Nahid Abdolrahmanpour

Thursday, February 1, 2024 - 13:30 to 14:30

Unveiling the Potential of Deep Reinforcement Learning (DRL): Methods and Applications.

Presenter:  Nahid Abdolrahmanpour

Date: Thursday, February 1, 2024

Time:  1:30 pm - 2:30pm

Location: 4th Floor (Workshop space) at 300 Ouellette Avenue (School of Computer Science Advanced Computing Hub)

 

LATECOMERS WILL NOT BE ADMITTED once the presentation has begun.

 

Abstract:

 Deep Reinforcement Learning (DRL) has become a groundbreaking paradigm in artificial intelligence, exhibiting the potential to solve complex decision-making tasks. This workshop aims to provide participants with a complete understanding of the methods and applications of DRL, highlighting its significance in various domains, including robotics, gaming, and autonomous systems.  Additionally, the workshop will delve into recent advancements and prospects, empowering participants to unlock the full capabilities of DRL and its transformative impact on the technological landscape.
 

Workshop Outline:

  • What is RL?
  • Basics of RL
  • Deep RL
  • DQN algorithms
  • Limitations
  • Future of DRL

 

Prerequisites:

  • Basic Programming Knowledge
  • Familiarity with Machine Learning Concepts
  • Interest in Artificial Intelligence

 

Biography: 

I am Nahid Abdolrahmanpour (Ph.D. Student in Computer Science) at the University of Windsor, With a solid foundation in Data Mining and Artificial Intelligence.

Research Focus: Social Network Analysis

I have already earned a master's degree in Computer

Science, specializing in Data Mining.