Reinforcement Learning using Kalman Filters
説明
In this investigation, we discuss a game of pursuit-evasion, or a hunter-prey problems using Q-learning framework. This has always been a popular research subject in the field of robotics where a hunter moves around in pursuit a prey. We involve Kalman filters to estimate the prey's status (location and velocity) and learn Q-values based on the estimated status. We evaluate our approach by convergence of Q-values and capturing steps.
収録刊行物
-
- 2019 IEEE 18th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)
-
2019 IEEE 18th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC) 136-143, 2019-07-01
IEEE
