Comparing against Stockfish 8 in a paper released today and labeling it as "Stockfish" is bordering on being dishonest. The current stockfish version (14) would make AlphaZero look bad, so they don't include it ...
> one of the strongest and most widely-used programs is Stockfish [81].
Here's the citation, note the date:
> [81] The Stockfish Development Team. Stockfish: Open source chess engine, 2021. https://stockfishchess.org/.
They mention the version number only once, further down, and don't point out that it's out of date since February 2018. All other 11 mentions of it don't have the version number, like in that sentence:
> In Chess, PoG(60000,10) is stronger than Stockfish using 4 threads and one second of search time.
Yeah, so it is! I guess I ran into the same weirdness as ShamelessC, since when I first Ctrl-F:ed the PDF, hit 1/11 was on page 11. Now that I try my damndest to reproduce it, I get 12 hits and the first is that one on page 10.
> Today, computer- playing programs remain consistently super-human, and one of the strongest and most widely-used programs is Stockfish.
They also go back to referring to it as Stockfish for the rest of the paper.
An analogous situation in my mind would be if AMD released a new CPU and benchmarked it against an Intel CPU, only mentioning once, somewhere in the middle of the paper, that it was a Pentium 4.
This is just a general effort to describe the present state of things. When they explicitly describe their evaluation process, they are sure to use the version number. They then _immediately_ drop the version number in subsequent usage which is culturally standard in research papers so they don't concern themselves with minute details of every single thing they find themselves redescribing. Believe me, you don't want to read the verbose version of this paragraph.
> In chess, we evaluated PoG against Stockfish 8, level 20 [81] and AlphaZero. PoG(800, 1) was run in training for 3M training steps. During evaluation, Stockfish uses various search controls: number of threads, and time per search. We evaluate AlphaZero and PoG up to 60000 simulations. A tournament between all of the agents was played at 200 games per pair of agents (100 games as white, 100 games as black). Table 1a shows the relative Elo comparison obtained by this tournament, where a baseline of 0 is chosen for Stockfish(threads=1, time=0.1s).
I also suspect part of the reason they chose Stockfish 8 was as a basis of comparison with AlphaZero. Their baselines for Go and poker are also pretty weak so their emphasis is clearly on displaying generality and reduced domain specialized input, not supremacy.
A single algorithm to play perfect and imperfect information games is difficult to achieve. Standard depth limited solvers and self-play RL result in highly exploitable agents. PoG appears to be very strong at Chess, decently strong at Go and decent at Poker (Facebook AI's ReBeL, the strongest prior work in this area, performed better against slumbot). What's unique about PoG is its ability to also play an imperfect information game (Scotland Yard) that has many rounds and a relatively long horizon (although it still has scaling issues).
It really isn't though. Technical papers have conventions, and they following them reasonably. You expect the methods description to be specific, the abstract not to be hyperbolic, and conclusions to be balanced. The general discussion parts are just that, general.
In the methods area they discuss the exact versions and parameters used, and how they compared them.
In the conclusions:
In the perfect information games of chess and Go,PoG performs at the level of human experts or professionals, but can be significantly weaker than specialized algorithms for this class of games, like AlphaZero, when given the same resources.
I don't know if the RAM bandwidth being much lower would have an impact on CPU benchmark though.
This is just benchmark cherry picking and does not reflect real performance or comparison.