ArztSamuel/Applying_EANNs

A 2D Unity simulation in which cars learn to navigate themselves through different courses. The cars are steered by a feedforward neural network. The weights of the network are trained using a modified genetic algorithm.

1.6k 371 +0/wk

GitHub

artificial-neural-networks deep-learning evolutionary-algorithms genetic-algorithm machine-learning neural-networks self-driving-cars

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Star & Fork Trend (21 data points)

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GitHub

stars 1.6k

forks 371

Growth Velocity

ArztSamuel/Applying_EANNs has +0 stars this period . Velocity data will be available after more historical data is collected.

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Metric	Applying_EANNs	DeepAA	rwkv.cpp	kotlindl
Stars	1.6k	1.6k	1.6k	1.6k
Forks	371	103	126	112
Weekly Growth	+0	+0	+0	+0
Language	ASP	Python	C++	Kotlin
Sources	1	1	1	1
License	MIT	MIT	MIT	Apache-2.0

Capability Radar vs DeepAA

Applying_EANNs

DeepAA

Maintenance Activity 0

Last code push 320 days ago.

Community Engagement 100

Fork-to-star ratio: 23.7%. 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.