Wasserstein Distance Maximizing Intrinsic Control

Wasserstein Distance Maximizing Intrinsic Control

28 October 2021

Stephen Spencer

Papers citing "Wasserstein Distance Maximizing Intrinsic Control"

4 / 4 papers shown

Title
Imagine, Verify, Execute: Memory-Guided Agentic Exploration with Vision-Language Models Seungjae Lee Daniel Ekpo Haowen Liu Furong Huang Abhinav Shrivastava Jia-Bin Huang LM&Ro 40 0 0 12 May 2025
CQM: Curriculum Reinforcement Learning with a Quantized World Model Seungjae Lee Daesol Cho Jonghae Park H. J. Kim 26 6 0 26 Oct 2023
Outcome-directed Reinforcement Learning by Uncertainty & Temporal Distance-Aware Curriculum Goal Generation Daesol Cho Seungjae Lee H. J. Kim 23 14 0 27 Jan 2023
Neuroevolution is a Competitive Alternative to Reinforcement Learning for Skill Discovery Félix Chalumeau Raphael Boige Bryan Lim Valentin Macé Maxime Allard Arthur Flajolet Antoine Cully Thomas Pierrot 24 21 0 06 Oct 2022