Action Guidance: Getting the Best of Sparse Rewards and Shaped Rewards
for Real-time Strategy Games

Action Guidance: Getting the Best of Sparse Rewards and Shaped Rewards for Real-time Strategy Games

5 October 2020

Santiago Ontañón

Papers citing "Action Guidance: Getting the Best of Sparse Rewards and Shaped Rewards for Real-time Strategy Games"

8 / 8 papers shown

Title
A Closer Look at Invalid Action Masking in Policy Gradient Algorithms Shengyi Huang Santiago Ontañón 59 316 0 25 Jun 2020
Mastering Complex Control in MOBA Games with Deep Reinforcement Learning Deheng Ye Zhao Liu Mingfei Sun Bei Shi P. Zhao ... Tengfei Shi Liang Wang Qiang Fu Wei Yang Lanxiao Huang 55 316 0 20 Dec 2019
Dota 2 with Large Scale Deep Reinforcement Learning OpenAI OpenAI : Christopher Berner Greg Brockman Brooke Chan ... Szymon Sidor Ilya Sutskever Jie Tang Filip Wolski Susan Zhang GNN VLM CLL AI4CE LRM 155 1,822 0 13 Dec 2019
Learning by Playing - Solving Sparse Reward Tasks from Scratch Martin Riedmiller Roland Hafner Thomas Lampe Michael Neunert Jonas Degrave T. Wiele Volodymyr Mnih N. Heess Jost Tobias Springenberg 85 448 0 28 Feb 2018
StarCraft II: A New Challenge for Reinforcement Learning Oriol Vinyals T. Ewalds Sergey Bartunov Petko Georgiev A. Vezhnevets ... Anthony Brunasso David Lawrence Anders Ekermo J. Repp Rodney Tsing 76 874 0 16 Aug 2017
Curiosity-driven Exploration by Self-supervised Prediction Deepak Pathak Pulkit Agrawal Alexei A. Efros Trevor Darrell LRM SSL 106 2,436 0 15 May 2017
Unifying Count-Based Exploration and Intrinsic Motivation Marc G. Bellemare S. Srinivasan Georg Ostrovski Tom Schaul D. Saxton Rémi Munos 167 1,478 0 06 Jun 2016
OpenAI Gym Greg Brockman Vicki Cheung Ludwig Pettersson Jonas Schneider John Schulman Jie Tang Wojciech Zaremba OffRL ODL 214 5,075 0 05 Jun 2016