ODSS: Efficient Hybridization for Optimal Coalition Structure Generation
Authors: Narayan Changder, Samir Aknine, Sarvapali Ramchurn, Animesh Dutta7079-7086
AAAI 2020 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | When compared to the state-of-the-art against a wide variety of value distributions, ODSS is shown to perform better by up to 54.15% on benchmark inputs. |
| Researcher Affiliation | Academia | 1National Institute of Technology Durgapur, India. 2LIRIS, Lyon 1 University, France. 3University of Southampton,UK. |
| Pseudocode | Yes | Algorithm 1 Subspace division technique; Algorithm 2 ODSS Algorithm |
| Open Source Code | No | The paper states that ODP-IP and ODSS were implemented in Java, and that they used code provided by the authors of ODP-IP. However, there is no explicit statement or link indicating that the code for ODSS is publicly available or open-source. |
| Open Datasets | No | The paper describes various data generation distributions (e.g., Agent-based Uniform, Chi-square) used for evaluation, but it does not refer to or provide access information for a specific publicly available or open dataset. |
| Dataset Splits | No | The paper describes running experiments with averages over 50 tests/runs for each distribution, but it does not specify explicit training, validation, or test dataset splits. |
| Hardware Specification | Yes | Both ODP-IP and ODSS were implemented in Java, and the experiments were run on an Intel(R) Xeon(R) CPU E7-4830 v3 with 160 GB of RAM. |
| Software Dependencies | No | The paper states that the implementation was done 'in Java' but does not provide specific version numbers for Java or any other software dependencies. |
| Experiment Setup | No | The paper describes the data generation distributions used for experiments but does not provide specific hyperparameters or system-level training settings for the algorithms, such as learning rates, batch sizes, or optimizer configurations. |