YavarYeganeh/Deep_AIF

Deep Active Inference (Deep AIF) Agents

30
/ 100
Emerging

This project offers an end-to-end probabilistic controller designed for complex industrial environments where decisions have delayed consequences and require long-term planning. It takes in real-time operational data from simulated industrial scenarios and outputs effective decisions for resource management and process control. Operations managers or industrial automation engineers can use this to automate and optimize decision-making.

No commits in the last 6 months.

Use this if you need an AI agent to make decisions in a dynamic industrial setting where actions have delayed effects and you need to plan hundreds of steps ahead without manually setting rewards or using expensive, exhaustive planning.

Not ideal if your environment involves simple, immediate cause-and-effect scenarios or if you prefer traditional, hand-coded control rules over a generative probabilistic model.

industrial-automation operations-management process-optimization predictive-control long-term-planning
Stale 6m No Package No Dependents
Maintenance 2 / 25
Adoption 4 / 25
Maturity 15 / 25
Community 9 / 25

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Stars

7

Forks

1

Language

Python

License

GPL-3.0

Last pushed

Oct 06, 2025

Commits (30d)

0

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