Multi-objective Optimization-based Selection for Quality-Diversity by Non-surrounded-dominated Sorting
Authors: Ren-Jian Wang, Ke Xue, Haopu Shang, Chao Qian, Haobo Fu, Qiang Fu
IJCAI 2023 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We perform experiments on synthetic functions and several complex tasks (i.e., QDGym, robotic arm, and Mario environment generation), showing that NSS achieves better performance than not only other MO-based selection methods but also state-of-the-art selection methods in QD. |
| Researcher Affiliation | Collaboration | 1State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China 2Tencent AI Lab, Shenzhen, China {wangrj, xuek, shanghp, qianc}@lamda.nju.edu.cn, {haobofu, leonfu}@tencent.com |
| Pseudocode | Yes | Algorithm 1 Non-surrounded-dominated Sorting |
| Open Source Code | Yes | Our code is available at https://github.com/lamda-bbo/NSS. |
| Open Datasets | Yes | We conduct experiments on four different environments, i.e., QD Hopper, Walker, Half Cheetah, and Ant. These tasks aim to generate a set of policies that move forward as fast as possible and are diverse in the frequency of feet use. Thus, the objective function is determined by the agent s forward speed, and the behavior descriptor functions are defined as the fraction of time each foot was touching the ground during an episode. |
| Dataset Splits | No | The paper discusses the iterative process of QD algorithms and performance metrics like QD-Score, but it does not specify any training, validation, or test dataset splits in the context of standard supervised learning benchmarks. |
| Hardware Specification | No | The paper does not provide specific details about the hardware used for the experiments, such as GPU models, CPU types, or memory specifications. It only discusses running time. |
| Software Dependencies | No | The paper mentions various algorithms and frameworks (e.g., ME, PGA-ME, OG-ME) but does not list any specific software dependencies or their version numbers, such as programming languages, libraries, or solvers. |
| Experiment Setup | Yes | The detailed settings of experiments are provided in Appendix B. |