fractional-quantum reinforcement learning DE
Fractional-Quantum Reinforcement Learning Differential Evolution for Large-Scale Edge Computing Offloading
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This study proposes a novel DE algorithm, termed fractional-quantum reinforcement learning differential evolution (FQRDE), to address these issues. The proposed method integrates fractional-order modeling, quantum-guided perturbation, and reinforcement learning–based strategy adaptation to enhance search effectiveness in complex optimization landscapes.
Main reference: Mingyang Yu, Jiaqi Zhang, Desheng Kong, Kairan Zhang, Shengwei Fu, Frank Jiang, Jing Xu, Fractional-Quantum Reinforcement Learning Differential Evolution for Large-Scale Edge Computing Offloading, Knowledge-Based Systems,2026.https://doi.org/10.1016/j.knosys.2026.116188.
Cite As
Mingyang (2026). fractional-quantum reinforcement learning DE (https://uk.mathworks.com/matlabcentral/fileexchange/183864-fractional-quantum-reinforcement-learning-de), MATLAB Central File Exchange. Retrieved .
General Information
- Version 1.0.0 (4.44 MB)
MATLAB Release Compatibility
- Compatible with any release
Platform Compatibility
- Windows
- macOS
- Linux
| Version | Published | Release Notes | Action |
|---|---|---|---|
| 1.0.0 |
