Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in Coakley et alK. L. Coakley, T. Snelleman, H. Hoos, and O. E. Gundersen, "The embrace of open science: An analysis of a decade of AI research and 56 800 conference papers," Under Review, 2026..
Learning in Online Principal-Agent Interactions: The Power of Menus
Authors: Minbiao Han, Michael Albert, Haifeng Xu
AAAI 2024 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We provide a thorough investigation of several online principal-agent problem settings and characterize their sample complexities, accompanied by the corresponding algorithms we have developed. and We propose the following algorithm 1 to learn the agent s true type 2 in log | | rounds. |
| Researcher Affiliation | Academia | 1Department of Computer Science, The University of Chicago 2Darden Business School, University of Virginia |
| Pseudocode | Yes | Algorithm 1: LEARNING-VIA-MENU and Algorithm 2: LEARNING-VIA-SINGLE-STRATEGY |
| Open Source Code | No | The paper does not provide concrete access to source code (specific repository link, explicit code release statement, or code in supplementary materials) for the methodology described. |
| Open Datasets | No | The paper is theoretical and does not involve empirical experiments with datasets that would require providing access information for training data. |
| Dataset Splits | No | The paper is theoretical and does not involve empirical experiments with datasets that would require providing specific dataset split information for validation. |
| Hardware Specification | No | The paper is theoretical and does not mention any specific hardware used for running experiments. |
| Software Dependencies | No | The paper is theoretical and does not provide specific ancillary software details (e.g., library or solver names with version numbers) needed to replicate experiments. |
| Experiment Setup | No | The paper is theoretical and does not describe an experimental setup with specific hyperparameter values or training configurations. |