Adrian

For normal random sampling,  you could use the
verb "normalrand" in
system\packages\stats\statdist.ijs  - that's if you're
using J602.

Don't forget that uniform or triangular
distributions often serve the purpose for these
sorts of applications.

NB - for old hands: It's not clear to me where the
equivalent can be found in the new J7 setup.  I can't
find "statdist.ijs" anywhere.  Are the old stats scripts
deplored?

Mike

On 28/03/2011 16:01, Adrian May wrote:
> On 28 March 2011 22:25, Raul Miller<[email protected]>  wrote:
>
>> Note that, personally, I do not know what you are trying to accomplish.
>> However if you are trying to build a list where each element is double
>>
>>
> No, it'll be those random numbers again. I'm trying to simulate the road
> that my neural network is gonna try to drive along. It should wind back and
> forth more or less like real roads. The list I'm making is a set of values
> for the curvature at each moment in time (the car's speed is constant for
> now.) So each value is a small random change to the previous one, with a bit
> of tuning if I can be bothered. I'm thinking of choosing the change in
> curvature from a normal distribution biased towards going straight again. I
> can't have the curvature go off the scale. Any off-the-shelf normal
> distribution functions?
>
> That'll be one of the inputs, there'll be more inputs, outputs and weights
> but otherwise the structure is pretty much like the last program. If it gets
> near the edge of the road or turns the wheel too hard the car becomes
> increasingly unstable, so by the same principle as the last network it
> should learn the most predictable strategy.
>
> At some point I'll want to calculate the road curvature some way ahead of
> everything else so the NN can see the road ahead.
>
> I just realised that I can't acquire a huge list of snapshots because this
> thing might take a hell of a long time to learn. Maybe the printing hack was
> right: at least it saved memory. I have no use for the old values.
>
> I guess I should stick to the existing architecture but add stuff to the
> environment function that has nothing to do with the outputs but carries
> some state of its own along and feeds a subset of that state to the inputs.
> That makes this whole thread redundant. Sorry for the distraction.
>
> Adrian.
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