Seed Selection in the Heterogeneous Moran Process
Authors: Petros Petsinis, Andreas Pavlogiannis, Josef Tkadlec, Panagiotis Karras
IJCAI 2024 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | An experimental evaluation of the greedy algorithm along with various heuristics on real-world data sets corroborates our results. ... Here, we present our experimental evaluation of the Greedy algorithm and other network heuristics, varying the seed size k and the maximum mutant fitness mmax. |
| Researcher Affiliation | Academia | 1Department of Computer Science, Aarhus University, Aarhus, Denmark 2Computer Science Institute, Charles University, Prague, Czech Republic 3Department of Computer Science, University of Copenhagen, Copenhagen, Denmark |
| Pseudocode | No | The paper describes algorithms (e.g., Greedy algorithm) and their properties, but it does not include a structured pseudocode block, algorithm box, or flow chart. |
| Open Source Code | No | The paper refers to a full version on arXiv ([Petsinis et al., 2024]) for proofs, but it does not explicitly state that the source code for the methodology described is publicly available, nor does it provide a direct link to a code repository. |
| Open Datasets | Yes | We use four real-world networks from Netzschleuder, SNAP and Network Repository (Table 1). (1) Facebook: A Facebook ego network... (2) Colocation: A proximity network... (3) Mammalia: An animal-contact network... (4) Polblogs: A network of hyperlinks... |
| Dataset Splits | No | The paper describes using Monte Carlo simulations on real-world networks and mentions varying parameters like 'k' and 'mmax'. However, it does not specify explicit training, validation, or test dataset splits in the conventional sense of partitioning data for machine learning model development and evaluation. |
| Hardware Specification | No | The paper does not provide any specific details about the hardware (e.g., GPU models, CPU types, memory) used to conduct the experiments. |
| Software Dependencies | No | The paper mentions using 'Monte Carlo simulations' and evaluating 'Greedy algorithm' against 'heuristics' but does not specify any particular software libraries, frameworks, or their version numbers that were used. |
| Experiment Setup | Yes | All Monte Carlo simulations were run over 5000 iterations. ... We set the resident fitness to 1, while the mutant fitness of each node u is determined by sampling a uniform distribution m(u) U(1, mmax). |