Computing Optimal Mixed Strategies for Security Games with Dynamic Payoffs
Authors: Yue Yin, Haifeng Xu, Jiarui Gan, Bo An, Albert Xin Jiang
IJCAI 2015 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Experimental results show that both algorithms significantly outperform existing approaches. Our fifth contribution is detailed experimental analysis on the solution quality and computational efficiency of the proposed algorithms. |
| Researcher Affiliation | Academia | 1The Key Lab of Intelligent Information Processing, ICT, CAS 2University of Chinese Academy of Sciences, Beijing 100190, China 3University of Southern California, Los Angeles, CA 90007, USA 4School of Computer Engineering, Nanyang Technological University, Singapore 639798 5Department of Computer Science, Trinity University, San Antonio, TX 79968, USA |
| Pseudocode | Yes | Algorithm 1: COCO(I, b, e) Algorithm 2: Computing Z((u, v), t) |
| Open Source Code | No | The paper does not provide any statement or link indicating that the source code for the described methodology is publicly available. |
| Open Datasets | No | In each game, we sample piecewise linear value functions with at most two sections, i.e., the number of sections is randomly sampled in {1, 2}. If a value function is determined to have two linear sections, the discontinuity point will be randomly chosen in (0, te), then the values of the function at time 0, te and the discontinuity point will be randomly chosen in (0, 100], thus the value of a value function ranges in (0, 100]. |
| Dataset Splits | No | The paper describes generating synthetic data for experiments and evaluating algorithm performance across varying parameters, but it does not specify traditional training, validation, or test dataset splits. |
| Hardware Specification | No | The paper does not provide specific details about the hardware (e.g., CPU, GPU models, memory) used to run the experiments. |
| Software Dependencies | No | The paper mentions the use of Linear Programming (LP) but does not specify any software names or versions (e.g., LP solver, programming languages, libraries) used in the implementation or experiments. |
| Experiment Setup | Yes | We assume te = 100. In each game, we sample piecewise linear value functions with at most two sections... If a value function is determined to have two linear sections, the discontinuity point will be randomly chosen in (0, te), then the values of the function at time 0, te and the discontinuity point will be randomly chosen in (0, 100], thus the value of a value function ranges in (0, 100]. ϵ is fixed at 10. for x = 10, transfer time of resources is randomly generated in [ 10/2 , 10]. |