i’m doing my final year project at university on machine learning
algorithms for use on a simple game of tic-tac-toe and i am using Prolog
with the XPCE add-on for the GUI.
I just wanted to know if it is possible to code a multi-layer perceptron
with the backpropagation algorithm? it’s a coursework assignment for my
neural networks course which states we must use c++, java or perl but i
hate them all!
im also studying neural networks but my lecturer absolutely sucks (he
can’t speak english and he just reads the slides out without turning
once to face the students lol. His average is 41 slides per 30 mins!)
just hoping someone out there can help!!!
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You can most definately use backpropagation on a multilayer perceptron.
In fact, that is the standard way of training the network.
I am currently developing some code in Java for an article or set of
articles on neural networks. If you have any more detailed questions,
dont be afraid to ask.
in the algorithm on the backward pass when u are calucating the error
values, new biases and new weights, i dont understand the symbols in the
formula to update the new weights with the learning rate!
could u help me please?
Well there are many ways to do this, and many symbols to use to
represent what is going on, so you should really post the symbols to be
However I can still make a guess at some of what you might be having
I link to a couple of images that provide a common description.
They are both referenced from
This is an inherent problem with mathmatitions devising these rules,
they like to use one letter variables all the time. I will personally
spell things out a little clearer. With good use of pseudocode.
Nomad, consider writing the articles for DevMaster :D