If a bot could look at your rating
donb...@gte.net
I think the main advantage that human experts have
over computer programs is the ability to make a certain
play based on the skill level of the opponent.
In other words, a program like jellyfish plays exactly
the same against everyone, whereas human players can
make tactical adjustments.
But, on Fibs, a program can actually *see* how good you
are before the match even starts. Is there anything that
can be gained by knowing the players' ratings?
Of course. Here's an example. Suppose that:
jellyfish, rated 2000, is playing X, rated 1000, in a
4 point match. At some point, player X doubles and jf
owns the 2 cube. Now suppose the game turns into a race
and jellyfish is left with two checkers, one on the 2
point and one on the five point, while the opponent is left
with one checker on his one point. It's jellyfish's roll.
What to do. Double? There are 19/36 winning sequences for
jf, and this is its last chance to double.
But of course, if jf considers the difference in their
rating, doubling is a very bad move. The stakes are not
equal in this match. Player X stands to win something like
8 ratings points, jf maybe around 4.
In fact, jf would need to have an overwhelming advantage
to re-double, in order to make this a profitable game
in terms of ratings points.
I just think it would be interesting if this calculation
were included in a bot's positional analysis, to see if it
would significantly improve its rating.
The example I gave was a last roll type position. What
is not clear to me is how the ratings affect the cube decision
if the entire match is not about to be decided, i.e., say
it is 0-0 in 9 point match. Or what if the position is
not a race, should the rating affect the cube decision then?
Who knows?
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Claes Thornberg
> I just think it would be interesting if this calculation
> were included in a bot's positional analysis, to see if it
> would significantly improve its rating.
>
> The example I gave was a last roll type position. What
> is not clear to me is how the ratings affect the cube decision
> if the entire match is not about to be decided, i.e., say
> it is 0-0 in 9 point match. Or what if the position is
> not a race, should the rating affect the cube decision then?
> Who knows?
I know :)
The rating difference affects the match equity table, which in turn
affects cube decisions. Read Kit's excellent "How to play tournament
backgammon" for cube decisions in matches between equal players. For
cube decisions in unequal matches, just use other match equity
tables. Tomas Szabo has produced match equity tables based on
differences in FIBS-rating (http://sg3.organ.su.se/~tsz/equity.html).
It has been suggested to Harald Wittmann, the creator of loner and
mloner, to have them use equity tables based on rating differences.
However, I don't think he ever implemented this idea.
--
______________________________________________________________________
Claes Thornberg Internet: cla...@it.kth.se
Dept. of Teleinformatics URL: NO WAY!
KTH/Electrum 204 Voice: +46 8 752 1377
164 40 Kista Fax: +46 8 751 1793
Sweden
Brian Sheppard
donb...@gte.net wrote in article <8672676...@dejanews.com>...
> I think the main advantage that human experts have
> over computer programs is the ability to make a certain
> play based on the skill level of the opponent.
> In other words, a program like jellyfish plays exactly
> the same against everyone, whereas human players can
> make tactical adjustments.
Jake Jacobs and Walter Trice have written a book showing how
humans should handle the cube in an unequal match. See their
web page <http://homepage.interaccess.com/~itaewon/>
> But, on Fibs, a program can actually *see* how good you
> are before the match even starts. Is there anything that
> can be gained by knowing the players' ratings?
>
> Of course. Here's an example. Suppose that:
> jellyfish, rated 2000, is playing X, rated 1000, in a
> 4 point match. At some point, player X doubles and jf
> owns the 2 cube. Now suppose the game turns into a race
> and jellyfish is left with two checkers, one on the 2
> point and one on the five point, while the opponent is left
> with one checker on his one point. It's jellyfish's roll.
>
> What to do. Double? There are 19/36 winning sequences for
> jf, and this is its last chance to double.
> But of course, if jf considers the difference in their
> rating, doubling is a very bad move. The stakes are not
> equal in this match. Player X stands to win something like
> 8 ratings points, jf maybe around 4.
> In fact, jf would need to have an overwhelming advantage
> to re-double, in order to make this a profitable game
> in terms of ratings points.
It is possible to build a match equity table that shows your
chance of winning a match as a function of the difference in
your skill levels.
To my knowledge, JF does not use this capability. It is possible
that other programs do. It is not hard to do, since these programs
have match equity calculators already.
Another dimension is checker play. Stronger players should aim
for complex, dynamic positions where things are "up in the air."
Computer programs are stronger players, so they should strive
for complicated play. I do not know whether any programs do this.
It is harder to implement than the cube-handling trick above.
One approximation could be to choose opening plays on the basis of
one's opponent, and after that allow the program to play its natural
moves.
Another dimension of human play is modifying your behavior based
upon observed weaknesses in the opponent. For instance, if you
are not sure whether to double or not, you might be swayed by
the fact that the opponent incorrectly dropped a similar double.
This is hard to implement.
> I just think it would be interesting if this calculation
> were included in a bot's positional analysis, to see if it
> would significantly improve its rating.
I think you would be disappointed by the results. It may improve
the program's play, or it may not.
The problem is that programs are already playing so well, that it
is hard to change anything without making them weaker. The program
gives up equity every time it plays a non-optimal move. Will it
regain that equity by errors of the opponent? Or not?
The doubling cube provides us with examples and counterexamples.
For instance, in the last-roll situation you give it would be a
clear error to double. But please note the reason why it would be
an error: the opponent is presumed to make the correct take/drop
decision.
But in general a weak opponent cannot be presumed to make correct
take/drop decisions. What do you do then?
Some players (Kit Woolsey?) have argued that being more aggressive
with the cube pays dividends because weaker players make two
characteristic errors:
1) They often drop takeable doubles, and
2) Even if they correctly take, they are likely to botch the
game after that point.
Other players (Jacobs and Trice?) argue that the doubling cube
should be offerred more sparingly. These players back up their
assertions with match equity calculations. But are they assuming
an unrealistic percentage of correct take/drop decisions?
I don't know what the resolution should be. I think that it is
safe to use an opponent-adjusted match equity table for deciding
whether to take/drop. It is safe, though unenterprising, to offer
doubles strictly on the basis of theoretical equity.
My belief is that programs have plenty of room for improvement in
their equity judgment. IMO, adjusting the program to "play-the-man"
is not the biggest problem at this point.
Warm Regards,
Brian
Julian
In article <01bc87b7$06cd6420$3ac032cf@polaris>, Brian Sheppard
<bri...@mstone.com> writes
>Another dimension of human play is modifying your behavior based
>upon observed weaknesses in the opponent. For instance, if you
>are not sure whether to double or not, you might be swayed by
>the fact that the opponent incorrectly dropped a similar double.
>This is hard to implement.
Of course, a bot with this implemented could end up being hustled - you
make deliberate but not ghastly errors early on in a match, with the aim
of pushing the bot into the "I've got an inferior opponent so I'm going
to make non-optimal plays to exploit his weakness" mode...
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Julian Hayward 'Booles' on FIBS jul...@ratbag.demon.co.uk
+44-1344-640656 http://www.ratbag.demon.co.uk/
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