Revenue Maximization Envy-Free Pricing for Homogeneous Resources
Authors: Gianpiero Monaco, Piotr Sankowski, Qiang Zhang
IJCAI 2015 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We provide upper and lower bounds for item and bundle pricing for the two notions of envy-freeness. The results are summarized in Table 1. Although, the problems studied here are rather basic, some of them are quite challenging. The envy-freeness requires that, given an uniform price per item, each buyer gets the number of items that maximizes his utility. The main result is to solve the EFIP-MUL problem optimally via a dynamic programming for general valuations. |
| Researcher Affiliation | Academia | Gianpiero Monaco University of L Aquila, Italy gianpiero.monaco@univaq.it Piotr Sankowski University of Warsaw, Poland sank@mimuw.edu.pl Qiang Zhang University of Warsaw, Poland qzhang@mimuw.edu.pl |
| Pseudocode | Yes | Algorithm 1: A logarithmic approximation algorithm for general valuations in PEFIP-MUL. Algorithm 2: A O(log n) approximation algorithm for non-decreasing valuations. |
| Open Source Code | No | The information is insufficient. The paper does not provide any specific links or statements regarding the availability of its source code. |
| Open Datasets | No | The information is insufficient. The paper is theoretical and does not describe experiments involving datasets for training. |
| Dataset Splits | No | The information is insufficient. The paper is theoretical and does not describe experiments involving datasets or their splits. |
| Hardware Specification | No | The information is insufficient. The paper is theoretical and does not describe any experiments that would require hardware specifications. |
| Software Dependencies | No | The information is insufficient. The paper is theoretical and does not provide specific software dependencies or version numbers for experimental replication. |
| Experiment Setup | No | The information is insufficient. The paper is theoretical and does not describe an experimental setup with hyperparameters or training configurations. |