2 citations · 2 across the 1 of their papers we have counts for
2 papers
cs.LG2022★ 2 cited
LECO: Learnable Episodic Count for Task-Specific Intrinsic Reward
Daejin Jo, Sungwoong Kim, Daniel Wontae Nam +4
Episodic count has been widely used to design a simple yet effective intrinsic motivation for reinforcement learning with a sparse reward. However, the use of episodic count in a h…
cs.AI2019
Creating Pro-Level AI for a Real-Time Fighting Game Using Deep Reinforcement Learning
Inseok Oh, Seungeun Rho, Sangbin Moon +3
Reinforcement learning combined with deep neural networks has performed remarkably well in many genres of games recently. It has surpassed human-level performance in fixed game env…