MU

Project-Group-BTP/Multi-UAV-Mobile-Edge-Computing-Hybrid-Optimization

Multi-UAV Assisted Wireless Powered Mobile Edge Computing: A hybrid optimization approach of combining multi-agent RL techniques (including attention mechanisms) with collaborative and adaptive caching policies for supporting mobile edge computing through UAVs.

89 10 +0/wk
GitHub
attention-mechanism caching deep-reinforcement-learning edge-computing gdsf-cache hybrid-optimization-methods maac maddpg mappo masac matd3 mobile-edge-computing
Trend 3

Star & Fork Trend (19 data points)

Stars
Forks

Multi-Source Signals

Growth Velocity

Project-Group-BTP/Multi-UAV-Mobile-Edge-Computing-Hybrid-Optimization has +0 stars this period . 7-day velocity: 2.3%.

Deep analysis is being generated for this repository.

Signal-backed technical analysis will be available soon.

Metric Multi-UAV-Mobile-Edge-Computing-Hybrid-Optimization data-ethics-club ai-evaluation ScalingOpt
Stars 89 898989
Forks 10 13301
Weekly Growth +0 +0+0+0
Language Python PythonPythonHTML
Sources 1 111
License MIT NOASSERTIONGPL-3.0N/A

Capability Radar vs data-ethics-club

Multi-UAV-Mobile-Edge-Computing-Hybrid-Optimization
data-ethics-club
Maintenance Activity 100

Last code push 6 days ago.

Community Engagement 56

Fork-to-star ratio: 11.2%. Active community forking and contributing.

Issue Burden 70

Issue data not yet available.

Growth Momentum 30

No measurable growth in the current period (first-day cold start expected).

License Clarity 95

Licensed under MIT. Permissive — safe for commercial use.

Risk scores are computed from real-time repository data. Higher scores indicate healthier metrics.

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