Venue: ICAPS 2020 Workshop HSDIP

Reviews:

final_score: rating: null
review_content: The revised version addresses almost all comments from the initial assessment
(point 3 from Reviewer 2 is not fully addressed) and I'm happy with the
changes, so still a clear accept from my side.

Minor remarks:
 - ZCP tie breaking: could you elaborate how pcf' is computed? Does it take the
 partial current iteration (or previous ones) into account?
 - Preliminaries: cost function A \mapsto ... -> \mathcal A
 - Footnote 1: What does "typically" mean here? Are there cases where tie
 breaking does not follow Fast Downward's variable order?
 - References: Franco et al. 2017 misses page numbers
review_title: Comments to revised version

final_score: rating: 8: Top 50% of accepted papers, clear accept
review_content: The paper analyzes variations of the well-known LM-cut heuristic. The first alteration considers an approximation of the cut that considers *all* incoming arcs into the goal zone, rather than just those that can be reached without entering the goal zone. While it can weaken the heuristic, it speeds up the heuristic computation. The second alteration considers different tie-breaking strategies for the precondition choice function, aimed at minimizing the size of the cut.

Overall, the paper is well written, the intuition behind the different tie-breaking strategies is explained very well, and the experimental evaluation is thorough and presents interesting results.

There are some minor questions I had while reading and which I think would be interesting if the authors elaborate on them in the paper:

1) Figure 3 shows a single data point where traditional cutting resulted 0 (I assume) expansions before the last f-layer, but around 10^6 expansions with the new cutting. Could you elaborate on this? From which domain is this? Did traditional cutting result in the perfect heuristic, and how much worse was the new cutting to cause so many evaluations?

2) Figure 4 shows that for some problems efficient cutting resulted in over 10 times higher expansions but you say the highest increase is up to 586% more expansions in Miconic. Is that number the average for the Miconic domain, or how do these numbers add up?

3) I am not sure I can follow the argument why in Synthesis the new cutting is slower. Is it that for traditional cutting, the actual cut is very small, i.e. many actions in the new cut can only be reached by going through the goal zone?

4) For the comparison against Scorpion, why was the h^2 preprocessor disabled? Did you want a "pure heuristic comparison", i.e. that both planners perform standard A*, just with different heuristics?
review_title: Initial assessment

final_score: rating: 7: Good paper, accept
review_content: I think it is a nice paper with interesting results that provide more insight
into the LM-Cut heuristic.
However, I think the following (rather minor) issues should be addressed:
1. Bonet and Helmert (2010) is correctly cited as proposing to use maximum of
multiple passes of LM-Cut heuristics with different pcfs. But this, in my
opinion, is not the main point of that paper (it is actually mentioned only in
the experimental section as a variant for comparison). The main point (that
should be briefly discussed in this paper) is that computing a hitting set on the
collection of all landmarks for all possible pcfs will result in h^+ (which in
itself is a good theoretical justification for trying different pcfs). And they
propose to use polynomial approximation of this approach.

2. I don't like the way the word "efficiency" is used (both in text and in the
title). It suggest that the paper introduces a new method that allows to
compute the (qualitatively) same landmarks, but faster (hence it increases
efficiency). But what is proposed in the paper is to trade quality (or
informativeness) for faster evaluation (i.e., it (over)approximates the original
method). I think "efficient cutting" should be changed to "faster cutting" or
"approximate cutting" or something like that, because "efficient cutting" is,
in my opinion, misleading.

3. In footnote 1, it is said that the LM-Cut variants had similar results if
they used the original cutting, but in the "Efficient Cutting" section, it is
said that using the new cutting increases coverage by 28 problems. I'm not
sure what is meant by that footnote.
Moreover, I would like to see more results on the comparison between the
original and new cutting technique. It would be nice to see at least:
(a) a scatter plot of heuristic values for initial states for the "arb"
variant, and (b) an additional column in the table (it should be renamed from
Figure to Table) with the results for "arb" with the original cutting (which
is the "vanilla" LM-Cut variant). But, of course, the more interesting results
can fit into the paper, the better.

4. Why is h^2 disabled for Scorpion planner? Is it because h^2 is not used for
the LM-Cut variants? It is not clear from the text.

5. What is "inv" variant? It is inverse of what? Of "arb" -- what does it
mean?

6. I don't understand why the number of evaluations per second for the
organic-synthesis domain is smaller with the new cutting technique. I don't
think the large number of actions explains it, because there is the same
number of actions for both variants and it should still (at least) halve the
number of the exploration cycles (only V^* is explored, V^0 and V^b is not
computed at all).
review_title: Initial assessment

Decision: Accept