2 papers
cs.LG2025
Multi-objective Reinforcement Learning with Nonlinear Preferences: Provable Approximation for Maximizing Expected Scalarized Return
Nianli Peng, Muhang Tian, Brandon Fain
We study multi-objective reinforcement learning with nonlinear preferences over trajectories. That is, we maximize the expected value of a nonlinear function over accumulated rewar…
cs.LG2024
Efficient and Scalable Deep Reinforcement Learning for Mean Field Control Games
Nianli Peng, Yilin Wang
Mean Field Control Games (MFCGs) provide a powerful theoretical framework for analyzing systems of infinitely many interacting agents, blending elements from Mean Field Games (MFGs…