Deep Curiosity Search: Intra-Life Exploration Can Improve Performance on
Challenging Deep Reinforcement Learning Problems

Deep Curiosity Search: Intra-Life Exploration Can Improve Performance on Challenging Deep Reinforcement Learning Problems

1 June 2018

Jeff Clune

Papers citing "Deep Curiosity Search: Intra-Life Exploration Can Improve Performance on Challenging Deep Reinforcement Learning Problems"

11 / 11 papers shown

Title
Goal Exploration via Adaptive Skill Distribution for Goal-Conditioned Reinforcement Learning Lisheng Wu Ke Chen 34 0 0 19 Apr 2024
Exploration via Elliptical Episodic Bonuses Mikael Henaff Roberta Raileanu Minqi Jiang Tim Rocktaschel OffRL 35 40 0 11 Oct 2022
An information-theoretic perspective on intrinsic motivation in reinforcement learning: a survey A. Aubret L. Matignon S. Hassas 42 35 0 19 Sep 2022
Exploration in Deep Reinforcement Learning: A Survey Pawel Ladosz Lilian Weng Minwoo Kim H. Oh OffRL 31 324 0 02 May 2022
Evolving Neural Networks with Optimal Balance between Information Flow and Connections Cost A. Khalili A. Bouchachia 17 0 0 12 Feb 2022
Exploration in Deep Reinforcement Learning: From Single-Agent to Multiagent Domain Jianye Hao Tianpei Yang Hongyao Tang Chenjia Bai Jinyi Liu Zhaopeng Meng Peng Liu Zhen Wang OffRL 41 93 0 14 Sep 2021
Active Reinforcement Learning over MDPs Qi Yang Peng Yang K. Tang 46 0 0 05 Aug 2021
First return, then explore Adrien Ecoffet Joost Huizinga Joel Lehman Kenneth O. Stanley Jeff Clune 47 352 0 27 Apr 2020
A Survey of Deep Reinforcement Learning in Video Games Kun Shao Zhentao Tang Yuanheng Zhu Nannan Li Dongbin Zhao OffRL AI4TS 43 188 0 23 Dec 2019
AI-GAs: AI-generating algorithms, an alternate paradigm for producing general artificial intelligence Jeff Clune 17 116 0 27 May 2019
Go-Explore: a New Approach for Hard-Exploration Problems Adrien Ecoffet Joost Huizinga Joel Lehman Kenneth O. Stanley Jeff Clune AI4TS 24 363 0 30 Jan 2019