Definition of the Discrimination Tree Algorithm
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Örjan Landgren
Dec 3, 2019, 8:35:37 AM12/3/19
to LearnLib Q&A
Hi!
I have been working for a number of weeks with LearnLib, and first I want to thank you for your extensive work and the fact that you share this project publicly!
I have been working for a number of weeks with LearnLib, and first I want to thank you for your extensive work and the fact that you share this project publicly!
Then I have at least one question: We are using LearnLib to compare the performance of available active learning algorithms that can be used on DFAs.
Looking at the LearnLib front page, four algorithms are available L*, KV, DT and TTT. So far we have found presentations of L* and KV and also TTT in a way so that we can understand it sufficiently enough but when it comes to the algorithm Discrimination Tree (DT) we have not been able to find any good description. Could you please help us with this?
Looking at the LearnLib front page, four algorithms are available L*, KV, DT and TTT. So far we have found presentations of L* and KV and also TTT in a way so that we can understand it sufficiently enough but when it comes to the algorithm Discrimination Tree (DT) we have not been able to find any good description. Could you please help us with this?
Yours sincerely
Örjan Landgren
Örjan Landgren
Markus Frohme
Dec 4, 2019, 12:58:55 AM12/4/19
to Örjan Landgren, LearnLib Q&A
Dear Örjan,
in short, you can think of the DT algorithm as the TTT algorithm without redundancy elimination of the discriminators. AFAIK the algorithm is sometimes also called "Observation Pack" algorithm and you can find its description in Falk's dissertation [0, chapter 2] (probably Falk knows best about this).
Kind regards,
Markus
[0] - http://hdl.handle.net/2003/29486
On Tue, Dec 03, 2019 at 05:35:37AM -0800, Örjan Landgren wrote:
> Hi!
>
> I have been working for a number of weeks with LearnLib, and first I want
> to thank you for your extensive work and the fact that you share this
> project publicly!
>
> Then I have at least one question: We are using LearnLib to compare the
> performance of available active learning algorithms that can be used on
> DFAs.
> Looking at the LearnLib <http://www.learnlib.de> front page, four
> You received this message because you are subscribed to the Google Groups "LearnLib Q&A" group.
> To unsubscribe from this group and stop receiving emails from it, send an email to learnlib-qa...@googlegroups.com.
> To view this discussion on the web visit https://groups.google.com/d/msgid/learnlib-qa/a7182ff3-13f0-4983-baba-53325b8e4591%40googlegroups.com.
in short, you can think of the DT algorithm as the TTT algorithm without redundancy elimination of the discriminators. AFAIK the algorithm is sometimes also called "Observation Pack" algorithm and you can find its description in Falk's dissertation [0, chapter 2] (probably Falk knows best about this).
Kind regards,
Markus
[0] - http://hdl.handle.net/2003/29486
On Tue, Dec 03, 2019 at 05:35:37AM -0800, Örjan Landgren wrote:
> Hi!
>
> I have been working for a number of weeks with LearnLib, and first I want
> to thank you for your extensive work and the fact that you share this
> project publicly!
>
> Then I have at least one question: We are using LearnLib to compare the
> performance of available active learning algorithms that can be used on
> DFAs.
> algorithms are available L*, KV, DT and TTT. So far we have found
> presentations of L* and KV and also TTT in a way so that we can understand
> it sufficiently enough but when it comes to the algorithm Discrimination
> Tree (DT) we have not been able to find any good description. Could you
> please help us with this?
>
> Yours sincerely
> Örjan Landgren
>
> --
> presentations of L* and KV and also TTT in a way so that we can understand
> it sufficiently enough but when it comes to the algorithm Discrimination
> Tree (DT) we have not been able to find any good description. Could you
> please help us with this?
>
> Yours sincerely
> Örjan Landgren
>
> You received this message because you are subscribed to the Google Groups "LearnLib Q&A" group.
> To unsubscribe from this group and stop receiving emails from it, send an email to learnlib-qa...@googlegroups.com.
> To view this discussion on the web visit https://groups.google.com/d/msgid/learnlib-qa/a7182ff3-13f0-4983-baba-53325b8e4591%40googlegroups.com.
Örjan Landgren
Dec 6, 2019, 3:46:17 AM12/6/19
to LearnLib Q&A
Dear Markus!
Thank you so much for your fast and helpful response!
Best regards,
Örjan
Thank you so much for your fast and helpful response!
Best regards,
Örjan
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