CoG 2021
Hierarchical Advantage for Reinforcement Learning in Parameterized Action Space
48 views
IEEE Conference on Games 2021
AI for Playing Games
Author: Zhejie Hu and Tomoyuki Kaneko
Title: Hierarchical Advantage for Reinforcement
Learning in Parameterized Action Space
AI for Playing Games
Author: Zhejie Hu and Tomoyuki Kaneko
Title: Hierarchical Advantage for Reinforcement
Learning in Parameterized Action Space
RELATED VIDEOS
CoG 2021
Gym-μRTS: Toward Affordable Deep Reinforcement Learning...
IEEE Conference on Games 2021 AI for Playing...
CoG 2021
Story Improvisation in Tabletop Roleplaying Games:...
Author: Devi Acharya, Michael Mateas and Noah...
CoG 2021
Honey, I Shrunk The Actor: A Case Study on Preserving...
IEEE Conference on Games 2021 AI for Playing...
CoG 2021
Multi-Agent Reinforcement Learning in Minecraft: Malmo
Author: Martin Balla, Marko Tot, Sam Devlin....