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Thanks Paul and Tomasz,
I have also used IO for many years and consulted with Fred on this
issue. Fred suggested using the Differential Evolution algorithm
rather than Particle Swarm when a system has many non-continuous
parameters.
In any case, Tomasz gave me the answer I needed regarding CMAE.
Thanks again,
Steve
--- In amibroker@xxxxxxxxxxxxxxx, "Paul Ho" <paul.tsho@xxx> wrote:
>
> Tomasz
>
> What you said and what I said can co-exist quite happily if you want
to read
> it again, and want to read it that way!
> It is not a debate that I want to enter into with you. I am just
sharing my
> experience - it is "possible" to do it.
> All of these IO used simulated "Continuous" parameters, which by its own
> nature are discrete, and it is the job of the user to get the best
use out
> of it.
>
> Finally, I have done tens of thousands of optimizations, lost of
them with
> success, so its about making your own luck in this game.
>
> for example consider this statement
> xyz = m1 * (MA(C, pds) > C) + (!m1) * (ma(c,pds) <= C);
> where m1 is a control parameters that decides whether xyz = ma(c,
pds) > C
> or the other way around, and pds is the period of ma, as it stands
it wont
> be get much "luck" as you say. because, pds that is optimimum in the
case of
> > is probably very different than in the case of <=.
> so by making xyz = m1 * (ma(c, pds1) > C) + (!m1) * (ma(c, pds2) <=
C); and
> optimize pds1, m1 and pds2 separately, you will get pds1 and pds2
gathering
> around a cluster of value closer to its optiminum, and m1 has own
value of 0
> or 1 which sort out what way is better.
>
> I hope this will be useful those who wants to use it.
>
>
> _____
>
> From: amibroker@xxxxxxxxxxxxxxx [mailto:amibroker@xxxxxxxxxxxxxxx]
On Behalf
> Of Tomasz Janeczko
> Sent: Wednesday, 1 October 2008 7:18 PM
> To: amibroker@xxxxxxxxxxxxxxx
> Subject: Re: [amibroker] Re: CMAE behavior when optimizing control
> parameters?
>
>
>
> Paul,
>
> I don't want to enter into yet another useless debate, but if you learn
> about
> *MATHEMATICAL* background of
> Particle Swarm Optimizers you will
> know that they are all designed to be used for CONTINUOUS parameter
spaces.
>
> The fact that non-exhaustive methods like CMAE, PSO, etc *may* work
in some
> cases for discrete spaces
> is more a question of luck and relative simplicity (or more or less
> "smoothness") of the problem
> being optimized than anything else.
>
> Best regards,
> Tomasz Janeczko
> amibroker.com
> ----- Original Message -----
> From: "Paul Ho" <paul.tsho@xxxxxx <mailto:paul.tsho%40gmail.com> com>
> To: <amibroker@xxxxxxxxx <mailto:amibroker%40yahoogroups.com> ps.com>
> Sent: Wednesday, October 01, 2008 11:03 AM
> Subject: [amibroker] Re: CMAE behavior when optimizing control
parameters?
>
> > Talking from personal experience - and I've been using intelligent
> > Optimizers for quite a number of years optimizing combinations of
> > continuous and "discrete" control parameters. Fred's IO has worked
> > extremely well - in that I'm able to find optiminiums successfully,
> > it may be a little more tricky, but not impossible. There are things
> > that would help to IO work better. Nevertheless, I do have more
> > problems with cmae with a lot of discrete parameters. But I suspect
> > that's more to do with configuration of cmae rather than the ability
> > of cmae itself.
> >
> > --- In amibroker@xxxxxxxxx <mailto:amibroker%40yahoogroups.com>
ps.com,
> "Tomasz Janeczko" <groups@>
> > wrote:
> >>
> >> No, CMAE, PSO and most other non-exhaustive methods
> >> are best for continuous parameter spaces. Discrete spaces
> >> where adjacent param values result in wild changes in fitness
> >> tend to be very difficult to optimize in "intelligent" manner.
> >>
> >> Best regards,
> >> Tomasz Janeczko
> >> amibroker.com
> >> ----- Original Message -----
> >> From: "Steve Davis" <_sdavis@>
> >> To: <amibroker@xxxxxxxxx <mailto:amibroker%40yahoogroups.com> ps.com>
> >> Sent: Wednesday, October 01, 2008 1:19 AM
> >> Subject: [amibroker] CMAE behavior when optimizing control
> > parameters?
> >>
> >>
> >> > Does anyone know if the CMAE algorithm can be used effectively to
> >> > optimize a system containing control parameters? By this I mean
> >> > optimizable parameters that do not measure a quantity, but are
> > instead
> >> > used to control the flow of execution of the program. In this
> > sort of
> >> > system, adjacent parameter values could result in wildly
> > different
> >> > system fitness.
> >> >
> >> > Thanks,
> >> > Steve
> >> >
> >> >
> >> >
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