Detailed Course Information |
Fall 2020
Apr 19, 2024 |
|
 |
||
| Select the desired Level or Schedule Type to find available classes for the course. |
| CSCI 2952H - Recent Progress in Reinforcement Learning |
|
Reinforcement learning is a framework for studying machines that interact with a sequential environment to achieve a goal. In the past decade, the RL framework has gained a lot of attention owing to its intriguing success in solving problems in complicated domains such as games, robotics, and dialog systems. We observe continual growth in the number of RL papers published in major machine-learning conferences. This growth calls for a careful investigation of the recent progress in the field. By reading selections of the current RL literature, this graduate-level course examines some of the latest theoretical and empirical progress in the field.
0.000 OR 1.000 Credit hours 0.000 OR 1.000 Lecture hours Levels: Graduate, Undergraduate Schedule Types: Discussion Section/Conference, Primary Meeting Computer Science Department Restrictions: Must be enrolled in one of the following Levels: Graduate |
| Return to Previous | New Search |
|