Historical milestone · 2019
AlphaStar
Reviewed through September 18, 2026
2019 · Historical milestone
AlphaStar
- Era
- 2010s
- Theme
- Multi-agent coordination
- Evidence form
- Peer-reviewed game experiment
- School / paradigm
- Population-based multi-agent reinforcement learning
- Institution / context
- Google DeepMind
- Researchers
- Oriol Vinyals; collaborators
Understand
Plain-language record, transferred from the reviewed source module.
Theory or experimental setup. Combined imitation learning, reinforcement learning, and league training against a population of evolving opponents.
Result / historical claim. Reached Grandmaster level in StarCraft II across all three races in the reported evaluation.
Apply
Professional implication, only where the reviewed record states one.
The checked-in record does not state a separate professional application for this entry. The topic page places it in the wider research lineage: Multi-agent coordination.
Verify
Evidence status, stated limitations, and the external sources this record actually carries.
Evidence form. Peer-reviewed game experiment
Limitation / debate. The result depended on one game, human replay priors, custom interfaces, and substantial compute.
Source status. The source link below is the verified link our reviewed topic research already carries for this milestone.
Reproduce
A reproduction tutorial is linked only when one exists for this exact record.
A reproduction tutorial is not yet available for this entry. The closest reviewed material is Multi-agent coordination.
Cite or share
APA-like: This historical record carries a year only, and no author or publisher of record in the checked-in data. An APA reference would have to invent that metadata.
BibTeX: BibTeX requires an author and publication venue. Historical lineage entries store a narrative record and its source link, not structured authorship, so the field would be fabricated.