Reinforcement Learning
Description: In this lecture, we will explore a different approach to learn from feedback. Reinforcement Learning is an alternative, and sometimes a complement, to supervised learning in which autonomous agents learn from interacting with the environment where they act. We will explore the theoretical and practical foundations of this approach.Department: Centro de Estudios y Asesorías en Estadística (CEASE)
Institution: Universidad de Nariño
Date: July 05, 2025
Hours: 4
From: 10:00 am
To: 12:00 am
Resources
Books
- Russell, S. and Norvig, P. (2010). Artificial Intelligence: A Modern Approach 3rd ed - Chapter 19 . Prentice Hall
- Lalanda, P. et al (2013). Autonomic Computing: Principles, Design and Implementation. Springer
- Sutton R. and Barto, A. (2020). Reinforcement Learning: An Introduction
Papers and Reports
- Silver D. et al. (2017). Mastering the game of Go without human knowledge
- Cabrera C. et al. (2019). A Self-Adaptive Service Discovery Model for Smart Cities
- Cabrera C. et al. (2021). A Reinforcement Learning-Based Service Model for the Internet of Things