A Better Algorithm for Societal Tradeoffs
Authors: Hanrui Zhang, Yu Cheng, Vincent Conitzer2229-2236
AAAI 2019 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | In this paper, we present a significantly improved algorithm and evaluate it experimentally. Our algorithm is based on a tight connection to minimum-cost flow that we exhibit. All experiments were done on a laptop computer with 8GB of memory and a 2.6 GHz Intel Core i5 CPU. Results are obtained by averaging over 10 runs with different seeds. For empirical evaluation, we implemented our algorithm based on the network simplex algorithm from LEMON (an open-source library of graph algorithms). |
| Researcher Affiliation | Academia | Hanrui Zhang Computer Science Department Duke University Durham, NC 27705 hrzhang@cs.duke.edu Yu Cheng Computer Science Department Duke University Durham, NC 27705 yucheng@cs.duke.edu Vincent Conitzer Computer Science Department Duke University Durham, NC 27705 conitzer@cs.duke.edu |
| Pseudocode | Yes | Algorithm 1: Translation from an Undirected Max-Cost Circulation optimum to a Societal Tradeoffs optimum. Algorithm 2: Translation from a Societal Tradeoffs optimum to an Undirected Max-Cost Circulation optimum. |
| Open Source Code | No | The paper mentions using "LEMON (an open-source library of graph algorithms)" and other solvers but does not state that the code for *their* method is open-source or provide a link to it. |
| Open Datasets | No | The paper states: "We generate input using 4 different distributions" and describes the generation process, but it does not refer to or provide access to a publicly available or open dataset. |
| Dataset Splits | No | The paper describes generating input data using 4 different distributions but does not specify training, validation, or test dataset splits (percentages, counts, or predefined splits) for reproducibility. |
| Hardware Specification | Yes | All experiments were done on a laptop computer with 8GB of memory and a 2.6 GHz Intel Core i5 CPU. |
| Software Dependencies | No | The paper mentions using "LEMON (an open-source library of graph algorithms)", "GNU Linear Programming Kit (GLPK)", and "CPLEX", but does not provide specific version numbers for these software components. |
| Experiment Setup | No | The paper describes the data generation distributions and the algorithms it compares against, but it does not provide specific hyperparameters or detailed system-level training settings for its own algorithm or the compared methods. |