Monday, November 21, 2005

GA/CTRNN Exercise for ALife Course

We've set-up an arguably minimal task where a CTRNN can be evolved to use its ability to integrate over time mildly interestingly as an exercise for EASy master's students.
The general aim of the activity is to get students to play with the evolution of dynamical systems controllers. The activity is incremental in that for their first activity they implemented a GA for a maxOne optimisation problem.

The big picture of the task is the following. You have to evolve a CTRNN to be able to calculate (or at least approximate) the rate of change of an input that comes into one 'input node' - and signal its 'best guess' by the activation on another node designated as the 'output node'. There may be some other internal nodes as well, and they may all be fully connected together. The evolutionary technique's job is to find a set of weights, biases and time-parameters for links and nodes, that make this an effective CTRNN at doing this job.

The task is sufficiently interesting because it requires the CTRNN to perform some integration over time, as opposed to (a) purely reactive behaviour (e.g. a phototactic robot) and (b) as opposed to merely computation (e.g. a 'xor' logic gate).

For more information on the task and my solution in C see here .


At 11:41 am, Blogger David said...

Hi Eduardo,

Mi name is David and I have try to access your example code without success. Can you help me on this?


At 11:49 am, Blogger eduardo said...

Dear David,

Try here:



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