3 papers
cs.AI2024
Hierarchical Multi-agent Meta-Reinforcement Learning for Cross-channel Bidding
Shenghong He, Chao Yu
Real-time bidding (RTB) plays a pivotal role in online advertising ecosystems. Advertisers employ strategic bidding to optimize their advertising impact while adhering to various f…
cs.AI2024
Offline Multi-Agent Reinforcement Learning via In-Sample Sequential Policy Optimization
Zongkai Liu, Qian Lin, Chao Yu +4
Offline Multi-Agent Reinforcement Learning (MARL) is an emerging field that aims to learn optimal multi-agent policies from pre-collected datasets. Compared to single-agent case, m…
cs.LG2024
An Offline Adaptation Framework for Constrained Multi-Objective Reinforcement Learning
Qian Lin, Zongkai Liu, Danying Mo +1
In recent years, significant progress has been made in multi-objective reinforcement learning (RL) research, which aims to balance multiple objectives by incorporating preferences…