Sean Sinclair, Felipe Frujeri, Ching-An Cheng, Luke Marshall, Hugo Barbalho, Jingling Li, Jennifer Neville, Ishai Menache, Adith Swaminathan
This code implements and evaluates algorithms for the paper Hindsight Learning for MDPs with Exogenous Inputs . In this paper we introduce Hindsight Learning, an algorithm to learn efficiently in a sub-class of MDPs coined MDPs with Exogenous Inputs.
@inproceedings{sinclair2023hindsight,
title={Hindsight Learning in MDPs with Exogenous Inputs},
author={Sinclair, Sean R. and Frujeri, Felipe and Cheng, Ching-An and Marshall, Luke and Barbalho, Hugo and Li, Jingling and Neville, Jennifer and Menache, Ishai and Swaminathan, Adith},
booktitle={arXiv},
year={2023},
}
This project is licensed under the terms of the MIT license.
The code is subdivided into three folders for the three different experiments conducted, including:
- Online Bin Packing (OBP)
- Airline Revenue Management (ARM)
- Multi Secretary (MS)
The Virtual Machine (VM) Allocation code is proprietary and thus is not included in the supplementary materials.
Contact srs429@cornell.edu to contribute.