CoG 2021
Proximal Policy Optimization with Elo-based Opponent Selection and Combination with Enhanced Rolling Horizon Evolution Algorithm
41 views
IEEE Conference on Games 2021
AI for Playing Games
Author: Rongqin Liang et al.
Title: Proximal Policy Optimization with Elo-based Opponent Selection and
Combination with Enhanced Rolling
Horizon Evolution Algorithm
AI for Playing Games
Author: Rongqin Liang et al.
Title: Proximal Policy Optimization with Elo-based Opponent Selection and
Combination with Enhanced Rolling
Horizon Evolution Algorithm
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
Multi-Agent Reinforcement Learning in Minecraft: Malmo
Author: Martin Balla, Marko Tot, Sam Devlin....
CoG 2021
Honey, I Shrunk The Actor: A Case Study on Preserving...
IEEE Conference on Games 2021 AI for Playing...