Solving Large-Scale Extensive-Form Network Security Games via Neural Fictitious Self-Play
Authors: Wanqi Xue, Youzhi Zhang, Shuxin Li, Xinrun Wang, Bo An, Chai Kiat Yeo
IJCAI 2021 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We conduct experiments in NSGs played on synthetic networks and real-world road networks. Our algorithm significantly outperforms state-of-the-art algorithms in both scalability and solution quality." and "4 Experimental Evaluation We firstly evaluate our algorithm on large-scale NSGs. Then, we perform ablation studies to understand how each component of NSG-NFSP affects the results. |
| Researcher Affiliation | Academia | Wanqi Xue1 , Youzhi Zhang2 , Shuxin Li1 , Xinrun Wang1 , Bo An1 and Chai Kiat Yeo1 1School of Computer Science and Engineering, Nanyang Technological University, Singapore 2Department of Computer Science, Dartmouth College, USA |
| Pseudocode | Yes | We provide the overall algorithm in the appendix. |
| Open Source Code | No | The paper does not provide concrete access to source code for the described methodology. |
| Open Datasets | Yes | We evaluate our algorithm in NSGs played on both artificially generated networks and real-world road networks. [...] We extract highways, primary roads and the corresponding intersections from Singapore map via OSMnx [Boeing, 2017]. [...] We generate the evaluation network by the grid model with random edges [Peng et al., 2013]. |
| Dataset Splits | No | The paper mentions training episodes for the DQN attacker (2 * 10^5) and testing episodes (2000), but does not specify a train/validation/test split for a dataset in terms of percentages or counts, or refer to standard predefined splits. |
| Hardware Specification | Yes | Experiments are performed on a server with a 10-core 3.3GHz Intel i9-9820X CPU and an NVIDIA RTX 2080 Ti GPU. |
| Software Dependencies | No | The paper mentions neural networks and deep learning concepts but does not specify any software names with version numbers, such as programming languages, libraries, or frameworks (e.g., Python, PyTorch, TensorFlow). |
| Experiment Setup | Yes | Neural network structures and hyperparameters are included in the appendix. |