EurekAlert!

Multi-constraint reinforcement learning in complex robot environments

FPMCO decomposes multi-constraint RL into KL-projection sub-problems, achieving higher reward with lower computing than second-order rivals on the new SCIG robotics benchmark.
GitHub

Reinforcement Learning Tuning for VideoLLMs: Reward Design and Data Efficiency

Understanding real-world videos with complex semantics and long temporal dependencies remains a fundamental challenge in computer vision. Recent progress in multimodal large language models (MLLMs) ...
GitHub

CapRL: Stimulating Dense Image Caption Capabilities via Reinforcement Learning

We are excited to release the CapRL 2.0 series: CapRL-Qwen3VL-2B and CapRL-Qwen3VL-4B. These models feature fewer parameters while delivering even more powerful captioning performance. Notably, ...
IEEE

FADQN: A Heuristic Reinforcement Learning Mechanism for UAV Path Planning in Unknown Environment

Abstract: Path planning remains a focal point in Unmanned Aerial Vehicle (UAV) research, with autonomous path planning in unknown environments emerging as a particularly active area. Deep ...
IEEE

Asymptotic Analysis of Sample-Averaged Q-Learning

Abstract: Reinforcement learning (RL) has emerged as a key approach for training agents in complex and uncertain environments. Incorporating statistical inference in RL algorithms is essential for ...