In this section
@inproceedings{Arulkumaran:2019:10.1145/3319619.3321894,
author = {Arulkumaran, K and Cully, A and Togelius, J},
doi = {10.1145/3319619.3321894},
pages = {314--315},
publisher = {ACM},
title = {AlphaStar: an evolutionary computation perspective},
url = {http://dx.doi.org/10.1145/3319619.3321894},
year = {2019}
}
TY - CPAPER
AB - In January 2019, DeepMind revealed AlphaStar to the world—thefirst artificial intelligence (AI) system to beat a professional playerat the game of StarCraft II—representing a milestone in the progressof AI. AlphaStar draws on many areas of AI research, includingdeep learning, reinforcement learning, game theory, and evolution-ary computation (EC). In this paper we analyze AlphaStar primar-ily through the lens of EC, presenting a new look at the systemandrelating it to many concepts in the field. We highlight some ofitsmost interesting aspects—the use of Lamarckian evolution,com-petitive co-evolution, and quality diversity. In doing so,we hopeto provide a bridge between the wider EC community and one ofthe most significant AI systems developed in recent times.
AU - Arulkumaran,K
AU - Cully,A
AU - Togelius,J
DO - 10.1145/3319619.3321894
EP - 315
PB - ACM
PY - 2019///
SP - 314
TI - AlphaStar: an evolutionary computation perspective
UR - http://dx.doi.org/10.1145/3319619.3321894
UR - http://hdl.handle.net/10044/1/70869
ER -
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