4 papers · 1 filter
COOPA: A Modular LLM Agent Architecture for Operations Research Problems
Chuanhao Li, Xiaoan Xu, Dirk Bergemann +3
Operations Research (OR) provides a rigorous framework for high-stakes decision-making, but effective OR modeling requires substantial domain knowledge, mathematical abstraction, a…
Learning in Context, Guided by Choice: A Reward-Free Paradigm for Reinforcement Learning with Transformers
Juncheng Dong, Bowen He, Moyang Guo +3
In-context reinforcement learning (ICRL) leverages the in-context learning capabilities of transformer models (TMs) to efficiently generalize to unseen sequential decision-making t…
In-Context Reinforcement Learning From Suboptimal Historical Data
Juncheng Dong, Moyang Guo, Ethan X. Fang +2
Transformer models have achieved remarkable empirical successes, largely due to their in-context learning capabilities. Inspired by this, we explore training an autoregressive tran…
Decoding Rewards in Competitive Games: Inverse Game Theory with Entropy Regularization
Junyi Liao, Zihan Zhu, Ethan Fang +2
Estimating the unknown reward functions driving agents' behaviors is of central interest in inverse reinforcement learning and game theory. To tackle this problem, we develop a uni…