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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@xxxxxxxxx>
To: <amibroker@xxxxxxxxxxxxxxx>
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@xxxxxxxxxxxxxxx, "Tomasz Janeczko" <groups@xxx>
> 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@xxx>
>> To: <amibroker@xxxxxxxxxxxxxxx>
>> 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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>
>
>
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> For NEW RELEASE ANNOUNCEMENTS and other news always check DEVLOG:
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*********************
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