- License: MIT
- Copyright: Copyright (c) SMC
http://smc.hit.edu.cn/
Structural Monitoring & Control
School of Civil Engineering
Harbin Institute of Technology
- DRL policy establishes a Deep Reinforcement Learning (DRL) framework for structural maintenance management by reformulating the problem as a standard control problem.
- With the great power of nonlinear representation of the DNNs, it is able to handle the decision-making in structural maintenance of large complex structures.
- The code is the detail implementation of paper Optimal policy for structure maintenance: A deep reinforcement learning framework.
- Two cases are provided here, the deck-system (for simple structures), and the long-span cable-stayed bridge (for complex structures).
