In a previous post, we looked at various features of a starting position such as the number of guaranteed turnovers and guaranteed suited turnovers. This means we can study two different starting positions and say that one is perhaps better than the other. However, ultimately we are interested in our chances of winning. If, for instance, my Dad was really awful at Spider and loses every game regardless of how good the start position is, the number guaranteed turnovers wouldn’t be particularly relevant.

Let us consider the following question: *what are the
chances of victory given we have N guaranteed turnovers at the start of the
game?* Obviously we would expect the more turnovers we start with, the
greater our chances of winning.

I guess the obvious thing to do would be to play 1 million games of Spider Solitaire on my PC, record the number of guaranteed turnovers at the start, play each game to the best of my ability without 85,78,68,79 and record the result (either win or loss). After all, I’m addicted to Spider Solitaire, my blog is about the Spider Solitaire, the whole Spider Solitaire and nothing but the Spider Solitaire, and I consider myself to be the world’s greatest expert on Spider Solitaire. Unfortunately, playing 1 million games is time-consuming even by my standards. Perhaps I could program an AI to play the games for me. After all, I have a math Ph. D., I have published a number of math-related papers, I have a steady job, and I know a programming language or three. Last year, I created a Flappy Bird cover of the famous Wintergatan Marble Machine using Matlab and Audacity …. Uh oh, I’ve just realised that designing an algorithm to play Spider well is not so trivial. So perhaps we could compromise by designing an AS, where S stands for Stupidity

**ENTER MY
FRIEND, NINJA MONKEY**

Fortunately I have an imaginary friend called *Ninja Monkey* (not to be confused with Monkey Magic) who is fluent in many languages such as Python-tongue (the language of pythons as well as other magical serpentine creatures), Javanese and C-plus-plus-speak. Thanks to an amazingly fast metabolism, Ninja Monkey is able to play 100 games of Spider Solitaire inside three minutes. On the down-side, his random move strategy is not very good, and he is yet to realise his dream of winning a single game of Spider Solitaire at the Four-Suit level. Nevertheless, he is able to win more than half the time if he pretends each game is played at the one-suit level. Not to mention that he is cute and friendly, and willing to give me a hug when I’m feeling down 😊

If you think about it, this gives us a way to estimate our chances of winning a game given a certain number of guaranteed turnovers. Given a large number of games, Ninja Monkey can record the number of guaranteed turnovers for a starting hand, play random moves pretending all cards are the same suit, report his result (win or loss). For instance, let us suppose that he plays 1000 games, 100 of which start with three turnovers. If NM wins 37 of those and loses the remaining 63, then we can reason that our winning chances are 37% given 3 turnovers. It’s likely not the most accurate estimate, but I guess we gotta start somewhere if you excuse the cliché!

With the help of my Ninja Monkey, I collated the following results

We immediately notice that the win ratio indeed increases as we increase our guaranteed turnovers. That is, if we ignore the division by zero error in column 9. That’s not so surprising when you think about it. After all, 9 turnovers implies a run of ten cards such as 3456789TJQ and the chances of starting with a run of ten cards are pretty slim. Also, there are very few games with 0 or 8 turnovers, so the stats are extremely reliable. With 1 or 7 turnovers we don’t have many data points so these may be doubtful. Around 4 turnovers, the results should be pretty reliable. I could have done more than 1000 iterations, but you get the gist.

**ADVANTAGES
OF AS OVER AI**

You may be justified in asking why anyone would be interested in an algorithm that just outputs random moves and can’t even beat my dad at chess.

It turns out Artificial Stupidity has some important advantages over its well-known brother of Artificial Intelligence. As I already alluded to earlier, it’s often easier to come up with an AS than an AI. Also, Artificial Stupidities are easier to replicate than Artificial Intelligence, so it is easy for Joe Bloggs to design his own algorithm and indeed confirm my figures are correct, or approximately correct. But we shouldn’t be dismissive of AI either. Beating the top human players at Go, Chess or Backgammon is no small feat. I believe that any artificial entity can be beneficial to humankind, whether it be intelligent or stupid – provided it is used for the right purpose!

Steve N Brown (the author of a Spider Solitaire book I alluded to in an earlier post) attempted to compile his own statistics for win ratio vs guaranteed turnovers. He got the following results

We immediately notice there are only 306 games instead of 1000, so it is not surprising that division by zero occurs for 8 or 9 guaranteed turnovers. Also, there is a weird drop to 0.37 win-ratio for 3 guaranteed turnovers. This either suggests 62 data points is insufficient or that Guaranteed Turnovers is a very poor indicator of the overall chance of winning at the Four-Suit level. After all Spider Solitaire is not a Scratch-n-win Lotto Ticket – you can’t win a prize just because you start with 10 good numbers; you’ve got to earn your prize! It is certainly possible for an expert to recover after a poor start (or conversely a beginner to 70,85,67,75 up after a good one). And of course I can’t blame Steve for not playing 1000 games.

Steve has also compiled similar stats for other features such as Suited Guaranteed Turnovers or multiplicity, but this is outside the scope of this blog post.

**SUMMARY**

I believe neither the Ninja Monkey or Steve Brown has a definitive answer to the question of what is the win rate as a function of number of guaranteed turnovers (assuming expert play sans 85,78,68,79). Playing at the 1-suit level is far too large a handicap for Ninja Monkey’s results to be meaningful and Steve has too few games to make reliable conclusions. So perhaps I *do* need to design an Artificial Intelligence that can play well at the Four-Suit level. Or someone else can design one. If the latter, I would be perfectly happy to recognise I am not the world’s greatest Spider player (but I would still consider myself a GM 😊 )

Despite the negative result, I wouldn’t call this experiment an exercise in futility. The journey is more important than the destination, and hopefully this is food for thought for the interested reader, if you excuse the numerous clichés. For now, it’s farewell to the Ninja Monkey. Hopefully we might meet him again in better times. Oh, and I’m still looking for a way to get in touch with Steve Brown – so if you know him (or even better, if you ARE him) please leave a comment!

Oh, if your name is Martin Molin and you like my Flappy Bird cover of the Marble Machine, please leave a comment too!