Increasing Generality in Machine Learning through Procedural Content Generation

29 November 2019

Papers citing "Increasing Generality in Machine Learning through Procedural Content Generation"

10 / 10 papers shown

Title
Causally Aligned Curriculum Learning Mingxuan Li Junzhe Zhang Elias Bareinboim CML 56 3 0 21 Mar 2025
Measuring Diversity of Game Scenarios Yuchen Li Ziqi Wang Qingquan Zhang Jialin Liu J. Liu 63 2 0 17 Jan 2025
Variational Offline Multi-agent Skill Discovery Jiayu Chen Bhargav Ganguly Tian-Shing Lan OffRL 58 1 0 26 May 2024
Powderworld: A Platform for Understanding Generalization via Rich Task Distributions Kevin Frans Phillip Isola OffRL 24 9 0 23 Nov 2022
Replay-Guided Adversarial Environment Design Minqi Jiang Michael Dennis Jack Parker-Holder Jakob N. Foerster Edward Grefenstette Tim Rocktaschel 116 94 0 06 Oct 2021
Active Reinforcement Learning over MDPs Qi Yang Peng Yang K. Tang 14 0 0 05 Aug 2021
Experience-Driven PCG via Reinforcement Learning: A Super Mario Bros Study Tianye Shu Jialin Liu Georgios N. Yannakakis 22 40 0 30 Jun 2021
Learning with AMIGo: Adversarially Motivated Intrinsic Goals Andres Campero Roberta Raileanu Heinrich Küttler J. Tenenbaum Tim Rocktaschel Edward Grefenstette 11 125 0 22 Jun 2020
Evolving Mario Levels in the Latent Space of a Deep Convolutional Generative Adversarial Network Vanessa Volz Jacob Schrum Jialin Liu Simon Lucas Adam M. Smith S. Risi GAN 65 229 0 02 May 2018
CAD2RL: Real Single-Image Flight without a Single Real Image Fereshteh Sadeghi Sergey Levine SSL 216 808 0 13 Nov 2016