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 [1].

The Pricing War Continues: On Competitive Multi-Item Pricing

Authors: Omer Lev, Joel Oren, Craig Boutilier, Jeffrey Rosenschein

AAAI 2015 | Venue PDF | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Theoretical We show this game may not always have a pure Nash equilibrium, in contrast to previous results for the special case where each vendor owns a single item. We do so by relating our game to an intermediate, discrete game in which the vendors only choose the available items, and their prices are set exogenously afterwards. We further make use of the intermediate game to provide tight bounds on the price of anarchy for the subset games that have pure Nash equilibria; we find that the optimal Po A reached in the previous special cases does not hold, but only a logarithmic one. Finally, we show that for a special case of submodular functions, efficient pure Nash equilibria always exist.
Researcher Affiliation Academia Omer Lev Hebrew University of Jerusalem Jerusalem, Israel EMAIL Joel Oren and Craig Boutilier University of Toronto Toronto, Canada EMAIL Jeffrey S. Rosenschein Hebrew University of Jerusalem Jerusalem, Israel EMAIL
Pseudocode No No pseudocode or algorithm blocks were found in the paper.
Open Source Code No The paper does not mention providing open-source code for its methodology.
Open Datasets No This is a theoretical paper and does not use datasets for training or empirical evaluation.
Dataset Splits No This is a theoretical paper and does not involve dataset splits for validation.
Hardware Specification No This is a theoretical paper and does not report on experiments requiring hardware specifications.
Software Dependencies No This is a theoretical paper and does not describe software dependencies with version numbers.
Experiment Setup No This is a theoretical paper and does not include details on experimental setup, hyperparameters, or training configurations.