Safe Mutations for Deep and Recurrent Neural Networks through Output
Gradients

Safe Mutations for Deep and Recurrent Neural Networks through Output Gradients

18 December 2017

Jeff Clune

Kenneth O. Stanley

Papers citing "Safe Mutations for Deep and Recurrent Neural Networks through Output Gradients"

7 / 7 papers shown

Title
Improving Deep Policy Gradients with Value Function Search Enrico Marchesini Chris Amato 23 9 0 20 Feb 2023
A Surrogate-Assisted Controller for Expensive Evolutionary Reinforcement Learning Yuxing Wang Tiantian Zhang Yongzhe Chang Bin Liang Xueqian Wang Bo Yuan 21 15 0 01 Jan 2022
Evolving Neural Networks through a Reverse Encoding Tree Haoling Zhang Chao-Han Huck Yang Hector Zenil N. Kiani Yue-Hong Shen Jesper N. Tegnér 16 5 0 03 Feb 2020
Deep Innovation Protection: Confronting the Credit Assignment Problem in Training Heterogeneous Neural Architectures S. Risi Kenneth O. Stanley 27 4 0 29 Dec 2019
Monte-Carlo Tree Search for Policy Optimization Xiaobai Ma Katherine Driggs-Campbell Zongzhang Zhang Mykel J. Kochenderfer 20 6 0 23 Dec 2019
Proximal Distilled Evolutionary Reinforcement Learning Cristian Bodnar Ben Day Pietro Lió 30 71 0 24 Jun 2019
Combating catastrophic forgetting with developmental compression Shawn L. E. Beaulieu Sam Kriegman Josh Bongard 25 4 0 12 Apr 2018