68 citations · 72 across the 2 of their papers we have counts for
3 papers
cs.AI2026★ 4 cited
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…
cs.AI2026★ 68 cited
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…
cs.LG2025
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…