3 papers
cs.LG2026
Inference-Time Policy Alignment for Fair Reinforcement Learning
Umer Siddique, Peilang Li, Conor Wallace +1
Deep reinforcement learning (RL) agents achieve strong performance by optimizing scalar reward functions. However, once deployed, the policies of these RL agents are often rigid an…
cs.MA2025
ReCollab: Retrieval-Augmented LLMs for Cooperative Ad-hoc Teammate Modeling
Conor Wallace, Umer Siddique, Yongcan Cao
Ad-hoc teamwork (AHT) requires agents to infer the behavior of previously unseen teammates and adapt their policy accordingly. Conventional approaches often rely on fixed probabili…
cs.MA2025
TransAM: Transformer-Based Agent Modeling for Multi-Agent Systems via Local Trajectory Encoding
Conor Wallace, Umer Siddique, Yongcan Cao
Agent modeling is a critical component in developing effective policies within multi-agent systems, as it enables agents to form beliefs about the behaviors, intentions, and compet…