Re: [Swarm-Modelling] GA question

[Rick Riolo]

i'm not quite sure what you are asking, but here is
one typical way that people use a GA (more generally, EA)
with a NN:

With an EA you generally want to have a population size P >> 1.
Each individual encodes the information for a set of weights
for one NN.  (i'm assuming the NN architecture is fixed.)
You use each individual NN to do whatever its supposed to do,
and rate it, i.e., assign it a fitness.
You do that for all P individuals (NNets).
Then you run a "generation" of the EA, to generate the
new population of individuals (NNets).
Repeat.

There are other similar approaches, of course.
(eg steady state GAs, etc).

I am not familiar the GA or NN libs that come with Swarm,
so i don't know about implementation.

- r


Rick Riolo                           address@hidden
Center for the Study of Complex Systems (CSCS)
4477 Randall Lab
University of Michigan         Ann Arbor MI 48109-1120
Phone: 734 763 3323                  Fax: 734 763 9267
http://cscs.umich.edu/~rlr

On Mon, 17 May 2004, DAVID CAMACHO wrote:

> Date: Mon, 17 May 2004 00:37:51 -0700 (PDT)
> From: DAVID CAMACHO <address@hidden>
> Reply-To: address@hidden
> To: address@hidden
> Subject: [Swarm-Modelling] GA question
>
>
> Hi everyone, I am developing an agent model based on the CRNN (continuous 
> time recurrent neural networks, implemented by J.J.Merello in Neurolib-2.1) 
> the actual model runs fine. But as mentioned for some authors, the best way 
> to improve their behaviour (changing weights and bias terms) is through a 
> Genetic Algorithm (there are also one GA, Breeder-2.1 developed by JJMerello) 
> but I don?t know how to implement it.  I have read the respective 
> documentation, witch is clear, but still some very basic things are not clear 
> to me, because I have no clue on GA.As far as I understood, the model to be 
> optimised, in this case the NN, should be created by the GA. As this model is 
> fixed, (I don?t want to optimised the architecture, it is ?full connection?, 
> nor the number of neurons) I suppose the GA should create just one copy of 
> the model. Which in turn should be utilized by the ?fitness function? to 
> evaluate the entire population of chromosomes (which represent the weights to 
> be optimis!
>  ed). If
>  this one copy supposition is right, still is not clear to me, if the model 
> should be reinitialised every time for the new set of weights, or a new model 
> as to be created.On the other hand, is all this is right, I suppose I have to 
> run the model in batch mode, but it  is the most important part for me, not 
> the GA. So how can I visualize the result?I hope some one can give me some 
> directions,Thanks,David Camacho
>
>
>
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