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 Shift Toward Open and Reproducible AI Research," Under Review, 2026. doi: 10.48550/arXiv.2606.16974..
Non-Myopic Negotiators See What's Best
Authors: Yair Zick, Yoram Bachrach, Ian A. Kash, Peter Key
IJCAI 2015 | Venue PDF | LLM Run Details | Input Tokens: 16,548 Total number of tokens sent to the LLM as input for this paper's analysis. | Output Tokens: 4,120 Total number of tokens produced by the LLM (including reasoning/thinking tokens) for this paper's analysis.
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We identify conditions that ensure that the socially optimal outcome is an ε-Nash equilibrium. We apply our results to some families of utility functions, and discuss their strategic implications. We formally prove this in a class of games called strategic negotiation games. |
| Researcher Affiliation | Collaboration | Yair Zick Carnegie Mellon University EMAIL Yoram Bachrach and Ian A. Kash and Peter Key Microsoft Research yobach,iankash,EMAIL |
| Pseudocode | No | The paper does not contain structured pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide concrete access to source code for the methodology described. |
| Open Datasets | No | The paper is theoretical and does not describe experiments using datasets. |
| Dataset Splits | No | The paper is theoretical and does not describe experiments with dataset splits. |
| Hardware Specification | No | The paper is theoretical and does not specify any hardware details used for experiments. |
| Software Dependencies | No | The paper is theoretical and does not specify any software dependencies with version numbers for reproducibility. |
| Experiment Setup | No | The paper is theoretical and does not describe a specific experimental setup, including hyperparameters or system-level training settings. |