3 papers
cs.LG2026
Partially Observable Multi-Agent Reinforcement Learning with Information Sharing
Xiangyu Liu, Kaiqing Zhang
We study provable multi-agent reinforcement learning (RL) in the general framework of partially observable stochastic games (POSGs). To circumvent the known hardness results and th…
cs.MA2026
Scaling Inference-Time Computation via Opponent Simulation: Enabling Online Strategic Adaptation in Repeated Negotiation
Xiangyu Liu, Di Wang, Zhe Feng +1
While large language models (LLMs) have emerged as powerful decision-makers across a wide range of single-agent and stationary environments, fewer efforts have been devoted to sett…
cs.LG2024
AdaFlow: Opportunistic Inference on Asynchronous Mobile Data with Generalized Affinity Control
Fenmin Wu, Sicong Liu, Kehao Zhu +7
The rise of mobile devices equipped with numerous sensors, such as LiDAR and cameras, has spurred the adoption of multi-modal deep intelligence for distributed sensing tasks, such…