Semestre 2021-18
| Nombre del curso: | Reinforcement Learning |
| Créditos: | 4 |
| Profesor: | Ivana Dusparic Nicolas Cardozo Alvarez |
| Horario: | 15 de Junio al 26 de Junio |
| (M,I,J,V) 12:30-17:15 | |
| Versión PDF | Click Aquí |
Descripción
In recent years Reinforcement Learning (RL) has resurfaced as one of the main drivers for AI, and in general decision making automation. RL is a powerful programming technique to enable long-term learning of software systems, being applicable to many different domains including robotics, software generation, testing, game playing, healthcare, and personalized assistants. In this course students will obtain theoretical and practical knowledge in underlying principles of RL, Markov decision processes, classic RL algorithms, and deep reinforcement learning. The course will also introduce current hot topics in advanced RL, such as transfer learning, multi objective learning, and explainability