AI models
Heuristic Reinforcement Learning
Training compute
1.1×10⁶ FLOP
Published
Oct 1, 1965
Heuristic Reinforcement Learning is an AI model developed by Purdue University (United States), first published in October 1965. It works in the robotics domain, on tasks such as system control.
Training it took an estimated 1.1×10⁶ FLOP of compute (estimation method: hardware).
Epoch AI rates the confidence of this record as speculative.
Full record
- Organization
- Purdue University
- Country of organization
- United States
- Domain
- Robotics
- Task
- System control
- Training compute
- 1.1×10⁶ FLOP
- Compute estimation method
- Hardware
- Training time
- 3 h
- Epoch confidence
- Speculative
SourceEpoch AI, 'AI Models'. Published online at epoch.ai. Retrieved 2026-07-29 from https://epoch.ai/data/ai-models. Licensed under CC BY 4.0.
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