Howto:Neural networks in Nasal: Difference between revisions
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= Links = | = Links = | ||
* http://en.wikipedia.org/wiki/Neural_network | |||
* http://en.wikipedia.org/wiki/Artificial_neural_network | |||
* http://www.cs.stir.ac.uk/~lss/NNIntro/InvSlides.html | |||
* http://www.willamette.edu/~gorr/classes/cs449/intro.html | |||
* http://www.psych.utoronto.ca/users/reingold/courses/ai/nn.html | |||
* http://www.doc.ic.ac.uk/~nd/surprise_96/journal/vol4/cs11/report.html | |||
* http://www.learnartificialneuralnetworks.com/#Intro | |||
* http://www.ibm.com/developerworks/library/l-neural/ | |||
* http://www.ai-junkie.com/ann/evolved/nnt1.html | |||
* http://www.heatonresearch.com/course/intro-neural-nets-cs | |||
* http://www.codeproject.com/KB/recipes/NeuralNetwork_1.aspx | |||
* http://www.codeproject.com/KB/recipes/brainnet.aspx | |||
== Vehicle control == | |||
* http://www.wired.com/medtech/health/news/2004/10/65438 | |||
* [http://mmi.tudelft.nl/pub/patrick/Liang.Q-CGAIDE2004.pdf TOWARDS A NEURAL CONTROL ARTIFICIAL PILOT] | |||
* [http://www.kbs.twi.tudelft.nl/Publications/Conference/2002/Ehlert.P.A.M-GAMEON2002.html Recognising situations in a flight simulator environment] | |||
* [http://soar.wichita.edu/dspace/handle/10057/883 Damage tests on an adaptive flight control system] | |||
* [http://www.neurones.espci.fr/Articles_PS/rivals2.pdf MODELING AND CONTROL OF MOBILE ROBOTS AND INTELLIGENT VEHICLES] | |||
* http://freespace.virgin.net/michael.fairbank/neuropilot/ |
Revision as of 08:07, 4 October 2011
Status: WIP/draft
Last update: 10/2011
Author/s: Hooray
topics to be covered
- pre-requisites (matrix maths)
- What are neural networks?
- advantages and disadvantages
- use cases in FlightGear (AI, bombable, combat etc)
- model of an artificial neuron
- number of 1-n inputs
- each input has one associated weight (positive/negative floating point factor)
- computation of activation value (foreach input)
- activation threshold
- output signal
- layering neural networks (input layer, processing layers, output layer)
- types of networks
- feedforward network
- backpropagation
- training a network
- types of NN training
- Implementing Neural Networks (NN) in Nasal
- using vectors of inputs and associated input weights
- using a Nasal hash as a helper object
- Mapping properties to neural inputs
- Mapping neural network outputs to properties
Links
- http://en.wikipedia.org/wiki/Neural_network
- http://en.wikipedia.org/wiki/Artificial_neural_network
- http://www.cs.stir.ac.uk/~lss/NNIntro/InvSlides.html
- http://www.willamette.edu/~gorr/classes/cs449/intro.html
- http://www.psych.utoronto.ca/users/reingold/courses/ai/nn.html
- http://www.doc.ic.ac.uk/~nd/surprise_96/journal/vol4/cs11/report.html
- http://www.learnartificialneuralnetworks.com/#Intro
- http://www.ibm.com/developerworks/library/l-neural/
- http://www.ai-junkie.com/ann/evolved/nnt1.html
- http://www.heatonresearch.com/course/intro-neural-nets-cs
- http://www.codeproject.com/KB/recipes/NeuralNetwork_1.aspx
- http://www.codeproject.com/KB/recipes/brainnet.aspx
Vehicle control
- http://www.wired.com/medtech/health/news/2004/10/65438
- TOWARDS A NEURAL CONTROL ARTIFICIAL PILOT
- Recognising situations in a flight simulator environment
- Damage tests on an adaptive flight control system
- MODELING AND CONTROL OF MOBILE ROBOTS AND INTELLIGENT VEHICLES
- http://freespace.virgin.net/michael.fairbank/neuropilot/