3 papers
cs.AI2025
Learning Human-Like RL Agents Through Trajectory Optimization With Action Quantization
Jian-Ting Guo, Yu-Cheng Chen, Ping-Chun Hsieh +4
Human-like agents have long been one of the goals in pursuing artificial intelligence. Although reinforcement learning (RL) has achieved superhuman performance in many domains, rel…
cs.AI2024
Identifying and Clustering Counter Relationships of Team Compositions in PvP Games for Efficient Balance Analysis
Chiu-Chou Lin, Yu-Wei Shih, Kuei-Ting Kuo +4
How can balance be quantified in game settings? This question is crucial for game designers, especially in player-versus-player (PvP) games, where analyzing the strength relations…
cs.RO2024
Gradient-based Regularization for Action Smoothness in Robotic Control with Reinforcement Learning
I Lee, Hoang-Giang Cao, Cong-Tinh Dao +2
Deep Reinforcement Learning (DRL) has achieved remarkable success, ranging from complex computer games to real-world applications, showing the potential for intelligent agents capa…