1. Brain Inspired Algorithms Dr. David Fagan
Neurocomputing
Brain Inspired Algorithms
Dr. David Fagan
MIS40980 Natural Computing & Applications

2. Basic Unit of the Computer
In computers we use transistors to perform computation
Once enough voltage is applied to the base, the connection between collector and emitter is established.
Foundation of all processors in computers.
MIS40980 Natural Computing & Applications

3. MIS40980 Natural Computing & Applications
Basic Unit of the Brain
MIS40980 Natural Computing & Applications

4. MIS40980 Natural Computing & Applications
Human Brain
Extremely complex computational device
Estimated 80 – 100 billion nerve cells in human brain
It takes 82,944 processors running a network of 1.73 billion cells with trillion synapses 40 minutes to perform 1 second of brain processing time. Using 1PB (1,000,000 GB) of memory!!!!! More here
MIS40980 Natural Computing & Applications

5. MIS40980 Natural Computing & Applications
Neural Networks
Neural Networks cover a wide variety of algorithms that take inspiration from the brain.
Key to all these networks is a general model of a Neuron (Perceptron)
MIS40980 Natural Computing & Applications

6. MIS40980 Natural Computing & Applications
Basic Neural Network
A neural network is essentially:
A composition of Perceptrons
Connected in different ways
Operating on different activation functions.
Glosser.ca
MIS40980 Natural Computing & Applications

7. MIS40980 Natural Computing & Applications
Neural Networks
Neurons
Bias
Training
Network Types
MIS40980 Natural Computing & Applications

8. MIS40980 Natural Computing & Applications
Neurons
Many different activation functions
Each one has different characteristics
MIS40980 Natural Computing & Applications

9. MIS40980 Natural Computing & Applications
Bias
Bias is a constant that is added to a layer, the value of which can be adjusted during training
Bias allows the network to shift the activation function, potentially allowing for better fitting of the neuron to the data, which may be critical for successful learning.
In most cases bias is helpful
MIS40980 Natural Computing & Applications

10. MIS40980 Natural Computing & Applications
Bias
MIS40980 Natural Computing & Applications

11. MIS40980 Natural Computing & Applications
Bias
MIS40980 Natural Computing & Applications

12. MIS40980 Natural Computing & Applications
Training
Getting a network to learn can be extremely difficult and slow.
Several approaches to training neural nets exist.
The most prevalent is Back propagation of Errors
This is used with some form of optimization method like gradient decent
MIS40980 Natural Computing & Applications

13. MIS40980 Natural Computing & Applications
Training
In Matlab they offer the following:
Levenberg-Marquardt
BFGS Quasi-Newton
Resilient Backpropagation
Scaled Conjugate Gradient
Conjugate Gradient with Powell/Beale Restarts
Fletcher-Powell Conjugate Gradient
Polak-Ribiére Conjugate Gradient
One Step Secant
Variable Learning Rate Backpropagation
Click here for more info
MIS40980 Natural Computing & Applications

14. MIS40980 Natural Computing & Applications
Learning Methods
Supervised Learning
Pattern Recognition, Classification), Regression, Speech and Gesture recognition.
Learning with a Teacher
Unsupervised Learning
Clustering, Estimation of Statistical Distributions, Compression and Filtering.
Some data is given and a cost function is used to drive the learning.
Reinforcement Learning
Control Problems, Games and Sequential Decision Making Tasks.
Learn by minimising / maximising gain with each interaction with environment
MIS40980 Natural Computing & Applications

15. MIS40980 Natural Computing & Applications
Network Types
Feed Forward NN
Auto Encoder
Recurrent Neural Nets
Restricted Boltzmann Machine
Many more… Google is your friend here!!!!!!! or click here
All based on similar fundamental
MIS40980 Natural Computing & Applications

16. Software for Neural Nets
Many Libraries Exist
For beginners I generally recommend PyBrain
Python based, easy to install and loads of documentation
Many more to pick from Theano, Caffe, TensorFlow, PyTorch
Give TensorFlow or PyTorch a go!!!!
MIS40980 Natural Computing & Applications

17. MIS40980 Natural Computing & Applications
Lets Play!!!!!!
The following is an interactive web based neural network that helps to show how networks behave during training
Tensor Flow Playground
MIS40980 Natural Computing & Applications

18. MIS40980 Natural Computing & Applications
Deep Neural Networks
In the past it was difficult to train large networks (time, computation, hardware)
Recent advances (GPU acceleration, large computational clusters etc.) have allowed for easier training of networks
Deep Networks simply refers to any network that has many layers (5+ layers)
Modern Deep Nets have many layers and take months/years to train
Deep Nets and Deep Learning are two different things!!!!!!
MIS40980 Natural Computing & Applications

19. MIS40980 Natural Computing & Applications
Deep Nets
Source
MIS40980 Natural Computing & Applications

20. MIS40980 Natural Computing & Applications
Deep Nets
Source
MIS40980 Natural Computing & Applications

21. MIS40980 Natural Computing & Applications
Deep Nets
Source
MIS40980 Natural Computing & Applications

22. Deep Neural Networks in the News
Google Deepmind – AlphaGo
Go is a very difficult game for computer
In January 2016 both Google and Facebook released results for there respective GO AI projects, indicating both were reaching levels never reached by previous AI’s
Google’s results where from Oct/Nov 2015
In March 2016 AlphaGo played 5 games against top human player Lee Sedol
AlphaGo only lost one game after it made a mistake but took several moves to realise this mistake at which point the game was beyond saving
Google had been training the AI against itself from Oct/Nov till March
Recently beat he world #1 ranked go player!!!!!!!!
MIS40980 Natural Computing & Applications

23. Deep Learning Examples
Check out this page that contains Deep ConvNets that run in your browser
ConvNetsJS
MIS40980 Natural Computing & Applications

24. Machine learning and Deep Neural Nets
Still confused?
Check out this video
Loads of courses and instructional videos available on Youtube
Same goes for online courses, just ask Google
MIS40980 Natural Computing & Applications

25. MIS40980 Natural Computing & Applications
Evolution + NN
NEAT
Evolution of Neural Networks using a GA to decide structure and weights etc.
Several version with most recent being HyperNEAT
MIS40980 Natural Computing & Applications