What is recorded here?
Combined human-game imitation with a league of main and exploiter policies, reaching Grandmaster-level results in evaluated online StarCraft II games for all three races.
Source-linked catalogue note. A detailed explanatory guide has not yet been prepared for this entry.
Scientific scope
Evaluation used stated camera and action constraints; result is not dominance in every match or transfer to arbitrary real-world multi-agent tasks.
Read the original work
- Grandmaster level in StarCraft II using multi-agent reinforcement learning
- Vinyals and colleagues: AlphaStar league-trained StarCraft II agent — official research record
- Publisher-deposited complete AlphaStar byline
This English explanation is an editorial reading view. It does not replace the complete original work or certify its science.
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People and systems
Oriol Vinyals; Igor Babuschkin; Wojciech M. Czarnecki; Michaël Mathieu; Andrew Dudzik; Junyoung Chung; David H. Choi; Richard Powell; Timo Ewalds; Petko Georgiev; Junhyuk Oh; Dan Horgan; Manuel Kroiss; Ivo Danihelka; Aja Huang; Laurent Sifre; Trevor Cai; John P. Agapiou; Max Jaderberg; Alexander S. Vezhnevets; Rémi Leblond; Tobias Pohlen; Valentin Dalibard; David Budden; Yury Sulsky; James Molloy; Tom L. Paine; Caglar Gulcehre; Ziyu Wang; Tobias Pfaff; Yuhuai Wu; Roman Ring; Dani Yogatama; Dario Wünsch; Katrina McKinney; Oliver Smith; Tom Schaul; Timothy Lillicrap; Koray Kavukcuoglu; Demis Hassabis; Chris Apps; David Silver
Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.
Research locations and affiliations
Location not yet established
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English catalogue narrative
Vinyals and colleagues: AlphaStar league-trained StarCraft II agent
Combined human-game imitation with a league of main and exploiter policies, reaching Grandmaster-level results in evaluated online StarCraft II games for all three races.
Scientific scope
Evaluation used stated camera and action constraints; result is not dominance in every match or transfer to arbitrary real-world multi-agent tasks.
Reading status
This is a source-linked WRS catalogue note. A full explanatory guide and independent scientific reconstruction have not been completed for this entry. Read the identified original work for its complete narrative and arguments.
People and systems
Oriol Vinyals; Igor Babuschkin; Wojciech M. Czarnecki; Michaël Mathieu; Andrew Dudzik; Junyoung Chung; David H. Choi; Richard Powell; Timo Ewalds; Petko Georgiev; Junhyuk Oh; Dan Horgan; Manuel Kroiss; Ivo Danihelka; Aja Huang; Laurent Sifre; Trevor Cai; John P. Agapiou; Max Jaderberg; Alexander S. Vezhnevets; Rémi Leblond; Tobias Pohlen; Valentin Dalibard; David Budden; Yury Sulsky; James Molloy; Tom L. Paine; Caglar Gulcehre; Ziyu Wang; Tobias Pfaff; Yuhuai Wu; Roman Ring; Dani Yogatama; Dario Wünsch; Katrina McKinney; Oliver Smith; Tom Schaul; Timothy Lillicrap; Koray Kavukcuoglu; Demis Hassabis; Chris Apps; David Silver
Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.