Crazy Stone Deep Learning first impressions

[oren]

I made a script...

Can you share it?

I will in a bit. I got it working late last night, and there are some things I would like to clean up first.

[Satorian]

I made a script that took the recording analysis from pdf printout and the original sgf to make comments and put CS's best move in as a triangle. The deltas aren't quite as big a swing as some of my bad kyu games, but I thought it was still fun to show off.

This is awesome! Was thinking about doing the exact same thing in Python.

Could you perhaps add two branches at the start, one for the black player, one for the white one, which then branch into the 5-6 moves/positions with the highest negative winrate delta, to have the game's top blunders in an overview?

[Amtiskaw]

I too am looking into making a tool to convert the analysis into something more useful. I don't seem to have the PDF option (maybe I need some Adobe stuff installed?) but I can export to OXPS, which is just a .zip file with relevant stuff inside it... I might have something working by tomorrow.

[Cassandra]

I don't seem to have the PDF option (maybe I need some Adobe stuff installed?) ...

Any free PDF writer / printer will do the job.

[Amtiskaw]

Alright here's a Python 3 script that works directly on an XPS / OXPS file from CrazyStone and converts it to SGF:

https://github.com/fohristiwhirl/crazys ... sis_to_sgf

If anyone succeeds or fails to use this, let me know.

[oren]

I ended up not cleaning it up much at all, but here is a dump of what I did.

https://github.com/oren740/go-tools/tre ... e-analysis

[dfan]

Amtiskaw's script worked for me, even though I'm on Windows 7 and thus have an .xps file rather than an .oxps file. Apparently the two formats are close enough.

[Amtiskaw]

There were some bugs in it, but they should be fixed now. I hope. Ugh, regular expressions.

I'll probably add some metadata extraction, since the XPS contains stuff like usernames.

[EDIT: Done. I also added hotspots in the SGF for moves CrazyStone found particularly bad. I recommend the Sabaki SGF editor for easily jumping to these.]

[LokBuddha]

Second game with 4 stones.
Strange that crazystone didn't resign and drag the game for 100+ moves

[LokBuddha]

another game 2 stones handicaps.

I won but this time, there is no problem, and crazy stones resign very early too. Too much aji keshi by CS. No global consideration from CS, and weak fighting tactically too... I don't think I played well either, quite a number of mistakes.

Can someone take a look at the game and review please?

Did I waste my $80 or my hardware too weak for Crazystone? I have i7-4790 3.6 ghz.

I'll try even game next.

[Amtiskaw]

my hardware too weak for Crazystone?

I'm under the impression that, when you select a level, it just uses whatever time needed to play "at that level".

[Krama]

Crazystone got demolished by Haylee. Such a disappointment.

[dfan]

I played a couple of quick games at the 5 kyu level. In both cases I had a comfortable opening lead, got lazy, got tricked tactically in a big life and death situation, and lost. I learned plenty from going over the ensuing analyses, so that's great. I did feel that it didn't play a lot like a 5 kyu human - lots and lots of pushing over and over, very little tenuki. This was just two games though. If I have to play people (or Crazy Stone on a higher level) to get more interesting fuseki, that's okay. On the other hand, in one game it "misread" a relatively straightforward life and death issue in a human sort of way, and so did I; in the analysis it was happy to point out what it "missed". (Scare quotes are all because of course it would have gotten it right running at full strength.)

I've been working my way up through its ranks and have won my last five games (W+R vs 4k, B+8.5 vs 3k, B+R vs 3k, W+14.5 vs 2k, W+R vs 2k). I'm curious how its strength setting is calibrated.

Its play has gotten more interesting as the rank has increased, unsurprisingly. I still feel like it has a pronounced tendency to get into pushing battles. That's pretty much the only way in which I feel like I can take advantage of its botness; I can sometimes encourage it into a pushing battle that I think benefits me. It is also often eager to capture a few stones while I make nice thickness that I think outweighs the sacrifice. Of course these traits are true of many humans as well at this level. I'm eager to see how it plays when I find a setting that beats me 50% of the time.

Going through its analysis interactively afterwards is extremely illuminating, and I feel like I have already learned a great deal, less about concrete variations, and more about what the interesting candidate moves (as we say in chess) are locally and where the biggest / most urgent area on the board is.

It's also nice to be able to play a relatively serious game in which I can think for a while without having to worry about finding a large uninterrupted chunk of time.

[OtakuViking]

Haven't tried any of the low levels, only 7d so I dunno how good the lower levels are.

I just wanted to mention that upping the priority in joblist is a good idea if you want crazystone to be stronger at 7d level unlimited time (it also plays significantly faster I found)
Unlike programs like leela, Crazystone doesn't utilize the CPU very efficiently or fully. Leela even continues searching nodes while the opponent plays and you can see how many nodes its searched + you can sort of make it search a ton of nodes (thus upping its strength alot) by giving it alot of time. Then when it's read out many many notes you can force it to move. I wish CSDL had this sort of functionality. CSDL is certainly stronger than leela, which is as it should be, but leela has some stuff in its base/free UI that I wish CSDL had... need more customizability to play round with tbh.

[Mike Novack]

I've been working my way up through its ranks and have won my last five games (W+R vs 4k, B+8.5 vs 3k, B+R vs 3k, W+14.5 vs 2k, W+R vs 2k). I'm curious how its strength setting is calibrated.

Are you playing with time controls?

When any of these programs are playing with time controls (X amount of time for Y moves) and so when coming up computes how much analysis they can do according to the power of the hardware the program finds itself running on then the strength levels cannot be absolute, just relative.

On the other hand, playing without time controls, setting how much analysis to use or what strength level to play at cannot know how much time will be required per move. Will simply use as much time as that depth of analysis requires when running on that hardware. For a given level of strength, hardware power and real time per move will be inversely proportional.