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Schneider Electric, AVEVA, Nscale and Start Campus pilot AI digital twin
Schneider Electric, AVEVA, Nscale and Start Campus pilot AI digital twin Engineering.com
Temporal Property-driven Design Space Exploration with Reinforcement Learning for Cyber-Physical Systems
A workflow for CPS design-space exploration using reinforcement learning is presented. The RL agent selects subsystem alternatives, and the model is evaluated via simulation with online temporal-property monitors.
Why it matters
Automating exploration of large design spaces for complex systems accelerates development and improves decision quality.
Relevant to DT products
- Original headline
- Temporal Property-driven Design Space Exploration with Reinforcement Learning for Cyber-Physical Systems
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