4 papers
Rule-Bottleneck Reinforcement Learning: Joint Explanation and Decision Optimization for Resource Allocation with Language Agents
Mauricio Tec, Guojun Xiong, Haichuan Wang +2
Deep Reinforcement Learning (RL) is remarkably effective in addressing sequential resource allocation problems in domains such as healthcare, public policy, and resource management…
On Sequential Fault-Intolerant Process Planning
Andrzej Kaczmarczyk, Davin Choo, Niclas Boehmer +2
We propose and study a planning problem we call Sequential Fault-Intolerant Process Planning (SFIPP). SFIPP captures a reward structure common in many sequential multi-stage decisi…
Multilinguality in LLM-Designed Reward Functions for Restless Bandits: Effects on Task Performance and Fairness
Ambreesh Parthasarathy, Chandrasekar Subramanian, Ganesh Senrayan +4
Restless Multi-Armed Bandits (RMABs) have been successfully applied to resource allocation problems in a variety of settings, including public health. With the rapid development of…
Finite-Horizon Single-Pull Restless Bandits: An Efficient Index Policy For Scarce Resource Allocation
Guojun Xiong, Haichuan Wang, Yuqi Pan +4
Restless multi-armed bandits (RMABs) have been highly successful in optimizing sequential resource allocation across many domains. However, in many practical settings with highly s…