A Bargaining Mechanism for One-Way Games
Authors: Andres Abeliuk, Gerardo Berbeglia, Pascal Van Hentenryck
IJCAI 2015 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We introduce one-way games, a framework motivated by applications in large-scale power restoration, humanitarian logistics, and integrated supplychains. The distinguishable feature of the games is that the payoff of some player is determined only by her own strategy and does not depend on actions taken by other players. We show that the equilibrium outcome in one-way games without payments and the social cost of any ex-post efficient mechanism, can be far from the optimum. We also show that it is impossible to design a Bayes Nash incentive-compatible mechanism for one-way games that is budget-balanced, individually rational, and efficient. Finally, we propose a privacypreserving mechanism that is incentive-compatible and budget-balanced, satisfies ex-post individual rationality conditions, and produces an outcome which is more efficient than the equilibrium without payments. |
| Researcher Affiliation | Academia | Andr es Abeliuk NICTA and University of Melbourne andres.abeliuk@nicta.com.au Gerardo Berbeglia NICTA and Melbourne Business School g.berbeglia@mbs.edu Pascal Van Hentenryck NICTA and Australian National University pvh@nicta.com.au |
| Pseudocode | No | The paper does not contain structured pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide an unambiguous statement or link for open-source code for the described methodology. |
| Open Datasets | No | The paper uses illustrative examples (Example 1, Example 2) for theoretical analysis and calculations, but does not mention the use of any public or open datasets for training or evaluation. No access information to any dataset is provided. |
| Dataset Splits | No | The paper is theoretical and does not describe experiments involving dataset splits for training, validation, or testing. |
| Hardware Specification | No | The paper does not explicitly describe the hardware used for any computational work or analysis. |
| Software Dependencies | No | The paper does not provide specific software dependencies or version numbers needed to replicate any computational work. |
| Experiment Setup | No | The paper is theoretical and does not describe an experimental setup with hyperparameters or system-level training settings. |