Bayesian Starcraft
No estimate
No hardware requirements for this model
The weights for this model have not been published, so it cannot be downloaded or run on your own hardware at any size. It is reachable only through its provider, and no graphics card changes that.
On record
Full specification
Everything on record for this model. Most of it describes how it was trained rather than how it runs — useful context for judging how much work went into it, and how it compares with models built at a different scale.
Origin
Who built this model, where, and when it was published.
- Organisation
- Collège de France
- Organisation type
- Academia
- Country
- France
- Published
- 31 August 2011
- Authors
- Gabriel Synnaeve, Pierre Bessière
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Games
- Task
- StarCraft
Size
How large the model is and how much data it was trained on. Parameters are the figure that decides whether it fits on a given graphics card.
- Parameters
- 13.1K
- Training data
- tokens
It's a bayes net, parameters are probabilty tables for probability that X happens in direction i given that we go in direction i. There are 25 directions.
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Citations
- 86
Sources
Where this record came from and when it was last checked.
- Reference
- A Bayesian Model for RTS Units Control applied to StarCraft
- Last updated
- 28 November 2025
What the numbers mean
What this model is
Bayesian Starcraft was published by Collège de France, in the country recorded as France, during August 2011. It comes out of an organisation categorised as academia.
It works in the domain of Games, and is recorded as performing the task of starCraft.
Its weights were never published, so it can only be reached through its provider. No graphics card changes that.
Answers
Bayesian Starcraft — common questions
Bayesian Starcraft— how many parameters does it have?
It has a parameter count of 13.1K. It's a bayes net, parameters are probabilty tables for probability that X happens in direction i given that we go in direction i. There are 25 directions. That figure is the total, and it is what decides how much memory the model needs — roughly half a gigabyte per billion at the compression most people use.
Bayesian Starcraft— who created it?
It was published by Collège de France, based in France, an organisation categorised as academia.
Bayesian Starcraft— when was it released?
It was published in August 2011. Capability per parameter has improved considerably since, so a newer model of the same size is often the better use of the same hardware.
Bayesian Starcraft— what is it used for?
It works in the domain of Games, and is recorded as handling the task of starCraft. A model can carry several of each, so these are the areas it was built for rather than a limit on what it will attempt.
Bayesian Starcraft— what GPU do I need to run it?
None. This is a closed model — its weights were never published, so it cannot be downloaded or run on your own hardware at any price. It is reachable only through its provider.
Bayesian Starcraft— is it open source?
The licensing was never recorded in our source data. We treat unstated licensing as closed, because an unrecorded licence is not one to rely on.
The other direction
Looking at it from the other side?
This page starts from the model. If you already own a card and want to know everything it will run, start from the hardware instead.