Punish/Reward
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
- IEEE
- Organisation type
- Industry
- Country
- Multinational
- Published
- 1 September 1973
- Authors
- Widrow, Gupta, and Maitra
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Games
- Task
- Blackjack
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
- 0K
- Training data
- tokens
Fig. 1 shows that there is a bias term, while Fig. 5 shows that the input is a sequence of 20 bits, corresponding to 20 weights. So the total number of parameters is 21.
??? Seemingly no info
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Citations
- 397
Sources
Where this record came from and when it was last checked.
- Reference
- Punish/Reward: Learning with a Critic in Adaptive Threshold Systems
- Last updated
- 28 November 2025
What the numbers mean
Where it came from
Punish/Reward was published by IEEE, in Multinational, in September 1973. It comes out of industry.
It works in Games, and is recorded as doing blackjack.
Its weights were never published, so it can only be reached through its provider. No graphics card changes that.
Answers
Punish/Reward — common questions
What is Punish/Reward used for?
Punish/Reward works in Games, and is recorded as handling blackjack. These are the areas it was designed around; they describe intent rather than a hard boundary.
What GPU do I need to run Punish/Reward?
None. Punish/Reward 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.
Is Punish/Reward open source?
The licensing for Punish/Reward was never recorded in our source data. We treat unstated licensing as closed, because an unrecorded licence is not one to rely on.
How many parameters does Punish/Reward have?
Punish/Reward has 0K parameters. Fig. 1 shows that there is a bias term, while Fig. 5 shows that the input is a sequence of 20 bits, corresponding to 20 weights. So the total number of parameters is 21. 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.
Who created Punish/Reward?
Punish/Reward was published by IEEE, based in Multinational, categorised as industry.
When was Punish/Reward released?
Punish/Reward was published in September 1973. Capability per parameter has improved considerably since, so a newer model of the same size is often the better use of the same hardware.
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.