143 citations · 159 across the 9 of their papers we have counts for
9 papers
Fairness-aware Multiobjective Evolutionary Learning
Qingquan Zhang, Jialin Liu, Xin Yao
Multiobjective evolutionary learning (MOEL) has demonstrated its advantages of training fairer machine learning models considering a predefined set of conflicting objectives, inclu…
State Space Closure: Revisiting Endless Online Level Generation via Reinforcement Learning
Ziqi Wang, Tianye Shu, Jialin Liu
In this paper, we revisit endless online level generation with the recently proposed experience-driven procedural content generation via reinforcement learning (EDRL) framework. In…
Keiki: Towards Realistic Danmaku Generation via Sequential GANs
Ziqi Wang, Jialin Liu, Georgios N. Yannakakis
Search-based procedural content generation methods have recently been introduced for the autonomous creation of bullet hell games. Search-based methods, however, can hardly model p…
Experience-Driven PCG via Reinforcement Learning: A Super Mario Bros Study
Tianye Shu, Jialin Liu, Georgios N. Yannakakis
We introduce a procedural content generation (PCG) framework at the intersections of experience-driven PCG and PCG via reinforcement learning, named ED(PCG)RL, EDRL in short. EDRL…
Deep Learning for Procedural Content Generation
Jialin Liu, Sam Snodgrass, Ahmed Khalifa +3
Procedural content generation in video games has a long history. Existing procedural content generation methods, such as search-based, solver-based, rule-based and grammar-based me…
A Hybrid Evolutionary Algorithm for Reliable Facility Location Problem
Han Zhang, Jialin Liu, Xin Yao
The reliable facility location problem (RFLP) is an important research topic of operational research and plays a vital role in the decision-making and management of modern supply c…
A Novel CNet-assisted Evolutionary Level Repairer and Its Applications to Super Mario Bros
Tianye Shu, Ziqi Wang, Jialin Liu +1
Applying latent variable evolution to game level design has become more and more popular as little human expert knowledge is required. However, defective levels with illegal patter…
Versatile Black-Box Optimization
Jialin Liu, Antoine Moreau, Mike Preuss +4
Choosing automatically the right algorithm using problem descriptors is a classical component of combinatorial optimization. It is also a good tool for making evolutionary algorith…
Interactive Evolution and Exploration Within Latent Level-Design Space of Generative Adversarial Networks
Jacob Schrum, Jake Gutierrez, Vanessa Volz +3
Generative Adversarial Networks (GANs) are an emerging form of indirect encoding. The GAN is trained to induce a latent space on training data, and a real-valued evolutionary algor…