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.
Watch cars learn to drive themselves through courses by using a neural network to navigate obstacles.
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Free · no card · unsubscribe anytimeA 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.
Applying_EANNs has 1.6k stars on GitHub. It has been forked 367 times. Applying_EANNs is written mainly in ASP. It has been in active development since 2017. Applying_EANNs is available under the MIT license. Its main topics are artificial-neural-networks, deep-learning, evolutionary-algorithms, genetic-algorithm.
What is 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.
Is Applying_EANNs open source?
Applying_EANNs is an open-source project. It is released under the MIT license.
Is Applying_EANNs free?
Yes. Applying_EANNs is free and open source — you can use, modify and self-host it.
What license does Applying_EANNs use?
Applying_EANNs is available under the MIT license.
What language is Applying_EANNs written in?
Applying_EANNs is written mainly in ASP.
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