4 papers
A Reward-Free Viewpoint on Multi-Objective Reinforcement Learning
Ying-Tu Chen, Wei Hung, Bing-Shu Wu +2
Many sequential decision-making tasks involve optimizing multiple conflicting objectives, requiring policies that adapt to different user preferences. In multi-objective reinforcem…
Semi-Supervised Cross-Domain Imitation Learning
Li-Min Chu, Kai-Siang Ma, Ming-Hong Chen +1
Cross-domain imitation learning (CDIL) accelerates policy learning by transferring expert knowledge across domains, which is valuable in applications where the collection of expert…
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…
Diminishing Exploration: A Minimalist Approach to Piecewise Stationary Multi-Armed Bandits
Kuan-Ta Li, Ping-Chun Hsieh, Yu-Chih Huang
The piecewise-stationary bandit problem is an important variant of the multi-armed bandit problem that further considers abrupt changes in the reward distributions. The main theme…