68 citations · 73 across the 4 of their papers we have counts for
4 papers
PA2D-MORL: Pareto Ascent Directional Decomposition based Multi-Objective Reinforcement Learning
Tianmeng Hu, Biao Luo
Multi-objective reinforcement learning (MORL) provides an effective solution for decision-making problems involving conflicting objectives. However, achieving high-quality approxim…
MO-MIX: Multi-Objective Multi-Agent Cooperative Decision-Making With Deep Reinforcement Learning
Tianmeng Hu, Biao Luo, Chunhua Yang +1
Deep reinforcement learning (RL) has been applied extensively to solve complex decision-making problems. In many real-world scenarios, tasks often have several conflicting objectiv…
RIDER: 3D RNA Inverse Design with Reinforcement Learning-Guided Diffusion
Tianmeng Hu, Yongzheng Cui, Biao Luo +1
The inverse design of RNA three-dimensional (3D) structures is crucial for engineering functional RNAs in synthetic biology and therapeutics. While recent deep learning approaches…
Beyond Monotonicity: Revisiting Factorization Principles in Multi-Agent Q-Learning
Tianmeng Hu, Yongzheng Cui, Rui Tang +2
Value decomposition is a central approach in multi-agent reinforcement learning (MARL), enabling centralized training with decentralized execution by factorizing the global value f…