Most AI systems are designed for one-off decisions: inference, image recognition, maintenance forecasts, anomaly detection, and so on.
But control systems need more than that.
They manage hardware exposed to changing local conditions, equipment aging, and unpredictable human intervention or even supply anomalies.
That’s where reinforcement learning comes in. It learns by doing. It will continually adapt its control strategies based on past outcomes and interactions. It handles delay, uncertainty and shifting conditions just as industrial environments face every day.
Some diverse example industries where there are real value gains are; Steel Manufacturing, Multi-energy Systems and Data Center Cooling.
If you’re ready to go beyond basic AI models, fixed rules and static logic, RL offers a way for systems to continuously learn and adapt to real-time conditions.
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