3 papers
cs.LG2024
PCGRL+: Scaling, Control and Generalization in Reinforcement Learning Level Generators
Sam Earle, Zehua Jiang, Julian Togelius
Procedural Content Generation via Reinforcement Learning (PCGRL) has been introduced as a means by which controllable designer agents can be trained based only on a set of computab…
cs.CV2024
Alpha-wolves and Alpha-mammals: Exploring Dictionary Attacks on Iris Recognition Systems
Sudipta Banerjee, Anubhav Jain, Zehua Jiang +3
A dictionary attack in a biometric system entails the use of a small number of strategically generated images or templates to successfully match with a large number of identities,…
cs.AI2023
Controllable Path of Destruction
Matthew Siper, Sam Earle, Zehua Jiang +2
Path of Destruction (PoD) is a self-supervised method for learning iterative generators. The core idea is to produce a training set by destroying a set of artifacts, and for each d…