Waiting for review: https://github.com/aibasel/downward/pull/244

I did a code review.

From the experiments, this doesn't seem to have much of an impact, so I want to ask a bit more about the motivation to test this.

You write "We used this option for combining the  "maximum factor"/"maximum SCP" scoring functions from the ICAPS 2024 paper (https://ai.dmi.unibas.ch/papers/sievers-et-al-icaps2024.pdf) with the SCC merge strategy". Who is "we" and where did you use it? In that paper itself?

If this was used in something somewhere, it would be good to add this to the documentation. Right now it's a bit hard to see the motivation for the change, as every option makes things a little bit more complicated.

Thanks! They look good to me.

@Silvan Here are the results of the experiments:

https://ai.dmi.unibas.ch/_experiments/ai/downward/issue1171/

@Gabi: everything is ready for experiments, except the modifications required for the cluster. Could you please run experiments? Or find some other volunteer? ;)

The pull-request is also ready for being reviewed: https://github.com/aibasel/downward/pull/244

I wanted to run some experiments, since I wanted to make the new option the default for the SCC merge strategy. I started preparing the scripts but I'll look into issue1173 first.

From my understanding (given the PR), is there any experiment planned for this 
issue or has it already been done? We found some issues with the parameter order 
in issue1173 regarding M&S that may affect them.

In the current implementation, the SCCs clusters are "worked on" one after the other, according to a used-specified order. In this issue, I'd like to add an option to allow merging the best candidate according to the used merge selector, where candidates stem from *all* SCC clusters. We used this option for combining the  "maximum factor"/"maximum SCP" scoring functions from the ICAPS 2024 paper (https://ai.dmi.unibas.ch/papers/sievers-et-al-icaps2024.pdf) with the SCC merge strategy.