2 papers
cs.LG2025
Application of linear regression and quasi-Newton methods to the deep reinforcement learning in continuous action cases
Hisato Komatsu
The linear regression (LR) method offers the advantage that optimal parameters can be calculated relatively easily, although its representation capability is limited than that of t…
cs.MA2023
Multi-agent reinforcement learning using echo-state network and its application to pedestrian dynamics
Hisato Komatsu
In recent years, simulations of pedestrians using the multi-agent reinforcement learning (MARL) have been studied. This study considered the roads on a grid-world environment, and…