Iocaine Powder
They were both poisoned.
Iocaine Powder is a heuristically designed compilation of strategies and
meta-strategies which took first place in Darse Billings' excellent
First
International RoShamBo Programming Competition. You may use its
source code freely; I ask only that you give me credit
for any derived works. I attempt here to explain how it works.
Meta-Strategy
RoShamBo strategies attempt to predict what the opponent will do. Given a
successful prediction, it is easy to defeat the opponent (if you know they will
play rock, you play paper). However, straightforward prediction will often
fail; the opponent may not be vulnerable to prediction, or worse, they might
have anticipated your predictive logic and played accordingly. Iocaine
Powder's meta-strategy expands any predictive algorithm P into six
possible strategies:
- P.0: naive application
- Assume the opponent is vulnerable to prediction by P; predict their next
move, and play to beat it. If P predicts your opponent will play rock, play
paper to cover rock. This is the obvious application of P.
- P.1: defeat second-guessing
- Assume the opponent thinks you will use P.0. If P predicts rock, P.0
would play paper to cover rock, but the opponent could anticipate this move
and play scissors to cut paper. Instead, you play rock to dull scissors.
- P.2: defeat triple-guessing
- Assume the opponent thinks you will use P.1. Your opponent thinks you will
play rock to dull the scissors they would have played to cut the paper you
would have played to cover the rock P would have predicted, so they will play
paper to cover your rock. But you one-up them, playing scissors to cut their
paper.
At this point, you should be getting weary of the endless chain. "We could
second-guess each other forever," you say. But no; because of the nature of
RoShamBo, P.3 recommends you play paper -- just like P.0! So we're only left
with these three strategies, each of which will suggest a different
alternative. (This may not seem useful to you, but have patience.)
- P'.0: second-guess the opponent
- This strategy assumes the opponent uses P themselves against you. Modify
P (if necessary) to exchange the position of you and your opponent. If P'
predicts that you will play rock, you would expect your opponent to play paper,
but instead you play scissors.
- P'.1, P'.2: variations on a theme
- As with P.1 and P.2, these represent "rotations" of the basic idea,
designed to counteract your opponent's second-guessing.
So, for even a single predictive algorithm P, we now have six possible
strategies. One of them may be correct -- but that's little more useful than
saying "one of rock, scissors, or paper will be the correct next move". We
need a meta-strategy to decide between these six strategies.
Iocaine Powder's basic meta-strategy is simple: Use past performance
to judge future results.
The basic assumption made by this meta-strategy is that an opponent will not
quickly vary their strategy. Either they will play some predictive algorithm
P, or they will play to defeat it, or use some level of second-guessing; but
whatever they do, they will do it consistently. To take advantage of this
(assumed) predictability, at every round Iocaine Powder measures how well each
of the strategies under consideration (six for every predictive algorithm!)
would have done, if it had played them. It assigns each one a score, using the
standard scoring scheme used by the tournament: +1 point if the strategy would
have won the hand, -1 if it would have lost, 0 if it would have drawn.
Then, to actually choose a move, Iocaine Powder simply picks the strategy
variant with the highest score to date.
The end result is that, for any given predictive technique, we will beat any
contestant that would be beaten by the technique, any contestant using the
technique directly, and any contestant designed to defeat the technique
directly.
Strategies
All the meta-strategy in the world isn't useful without some predictive
algorithms. Iocaine Powder uses three predictors:
- Random guess
- This "predictor" simply chooses a move at random. I include this algorithm
as a hedge; if someone is actually able to predict and defeat Iocaine Powder
with any regularity, before long the random predictor will be ranked with the
highest score (since nobody can defeat random!). At that point, the
meta-strategy will ensure that the program "cuts its losses" and starts playing
randomly to avoid a devastating loss. (Thanks to Jesse Rosenstock for
discovering the necessity of such a hedge.)
- Frequency analysis
- The frequency analyzer looks at the opponent's history, finds the move they
have made most frequently in the past, and predicts that they will choose it.
While this scores a resounding defeat against "Good Ole Rock", it isn't very
useful against more sophisticated opponents (which are usually quite
symmetrical). I include it mostly to defeat other competitors which use it as
a predictive algorithm.
- History matching
- This is easily the strongest predictor in Iocaine Powder's arsenal, and
variants of this technique are widely used in other strong entries. The
version in Iocaine Powder looks for a sequence in the past matching the last
few moves. For example, if in the last three moves, we played paper against
rock, scissors against scissors, and scissors against rock, the predictor will
look for times in the past when the same three moves occurred. (In fact, it
looks for the longest match to recent history; a repeat of the last 30 moves
is considered better than just the last 3 moves.) Once such a repeat is
located, the history matcher examines the move our opponent made afterwards,
and assumes they will make it again. (Thanks to Rudi Cilibrasi for introducing
me to this algorithm, long ago.)
Once history is established, this predictor easily defeats many weak
contestants. Perhaps more importantly, the application of meta-strategy allows
Iocaine to outguess other strong opponents.
Details
If you look at Iocaine Powder's source code, you'll discover additional
features which I haven't treated in this simplified explanation. For example,
the strategy arsenal includes several variations of frequency analysis and
history matching, each of which looks at a different amount of history; in some
cases, prediction using the last 5 moves is superior to prediction using the
last 500. We run each algorithm with history sizes of 1000, 100, 10, 5, 2,
and 1, and use the general meta-strategy to figure out which one does best.
In fact, Iocaine even varies the horizon of its meta-strategy analyzer!
Strategies are compared over the last 1000, 100, 10, 5, 2, and 1 moves, and
a meta-meta-strategy decides which meta-strategy to use (based on which picker
performed best over the total history of the game). This was designed to
defeat contestants which switch strategy, and to outfox variants of the simpler,
older version of Iocaine Powder.
Summary
One must remember, when participating in a contest of this type, that we are
not attempting to model natural phenomena or predict user actions; instead,
these programs are competing against hostile opponents who are trying very hard
not to be predictable. Iocaine Powder doesn't use advanced statistical
techniques or Markov models (though it could perhaps be improved if it did),
but it is very devious.
As a final word, note that any good strategy should have a random fallback (if
it's losing, start playing randomly). It's not possible to beat such a
strategy by very much, so a competition populated by entries designed by people
who realize this basic fact would be quite boring. Since it's the "dumb"
entries that make RoShamBo interesting, so the challenge is mostly to figure
out the things entrants who are not very bright will think of.
Dan Egnor