Poker
Academy takes advantage of the fact
that most of us learn best by doing.
With sophisticated computer
opponents, you will be able to play
thousands of hands to improve your
Texas Hold’em skills.
There are other places you can play
poker, but
Poker
Academy is your best choice for
learning. Sitting down at a real
money poker table, be it at a
casino, card room, or online,
provides a good learning experience
but can be very costly. And for
beginners just starting out, other
players may not be forthcoming with
advice that will help you beat them
in the long run.
When you
play online against other people on
a play money site you often find
that your opponents are not playing
their best game. They realize it is
not actual money and do not worry
about losing virtual dollars. They
very rarely fold, instead gambling
on hitting their long shot draws.
Playing against these types of
opponents can actually hurt your
poker game when you decide to make
the switch to real money -- beating
someone who doesn’t care about
losing is much different than
players trying their hardest to win.
Poker
Academy doesn’t share these
shortcomings. You don’t have to
perfect your game while risking
money at a casino. And the computer
opponents are sophisticated sparring
partners. They are not going to take
it easy on you because it is not
real money. What’s more they will
let you look at their cards, change
stakes, shuffle up the tables, play
with a full table, short-handed, or
heads up and are always at your beck
and call on your home computer or
laptop on the road. All without
complaining or giving anything but
their best. If you can get to the
point where you can consistently
beat the hardest opponents Poker
Academy has to offer, you will be
well prepared to take on the larger
poker world.
Playing a
large number of hands against
serious opponents will improve your
game. But you can improve faster by
studying some of the hands to a
greater depth. The Hand Evaluator
will let you load any current hand
and look at its specifics. It will
show you what the mathematical
strength of your hand is. You can
use that to look at how the computer
rates your hand. It allows you to
graphically adjust how loose or
tight your opponents as a group are
playing and see what that does to
the distribution of hands they are
likely to hold and whether or not
those hands beat yours. You can do a
quick simulation to try a large
number of combinations of future
board cards and hole cards to see
how many times you’d expect to win,
lose, or tie.
The Hand
Evaluator is not meant to be used on
every hand. Instead, players should
use it to analyze a particularly
tricky situation and to check from
time to time to see that their poker
intuition fits with mathematical
numbers.
Over the course
of a poker session you will play
many hands. How well did you do?
Much of the answer comes from
looking at your bankroll, and seeing
how much money you made (or lost). A
single number only gives you an
overview of the session however, and
you should take the time to look in
more detail where things went well,
or badly.
The Player
Statistics window allows you to take
a look at your bankroll over time,
as well as the bankrolls of the
computer opponents you played
against. The graph is not just a
pretty picture but a tool to help
you understand your wins and losses.
Did all of your wins come in a short
period of time or is it slow, steady
improvement? Do you have a large
drop somewhere in an otherwise
winning session? Perhaps one of the
opponents made a long shot on you
and you went on “tilt”.
Exclusive to
Poker Academy Pro is luck analysis.
Poker is a game of skill yet the
cards you hold are based on luck. It
is just as important to minimize
your losses when you get unlucky as
it is to maximize your gains when
the cards are on your side. In the
Player Statistic window you can
overlay the graph of your bankroll
with a measure of the luck of cards.
Were you just getting a bad run of
cards, or did you misplay a hand?
When your luck turns, do you adapt
quickly or assume for too long that
it will change back? What about the
AI players who are winning, is it
luck based or are they exploiting a
weakness in your game?
When you’ve
identified an area of the graph
where you played especially well or
especially poorly, it is a good idea
to look over that run of hands
again. To do this, you can open the
Hand History window and quickly flip
through a number of hands, reliving
the action and seeing what went
right and what went wrong. This time
you can optionally know all of your
opponents’ cards, and see the game
from their perspective.
As you
progress, you may have poker
questions that you’d like answered
without having to actually wait for
them to occur in a hand. How often
will my Ace-Ace hold up against his
7-8 suited? What about against 3
players with random hands? What are
the chances of me winning when I
have four cards to a straight and
flush on the flop, versus top two
pair? For questions like these,
Poker Academy Pro has the Showdown
Calculator.
The Showdown
Calculator lets you select up to ten
players, and set their cards to any
two cards, or unknown cards. The
board similarly can be set to any
combination of real cards and
unknown cards. You can then get
Poker Academy Pro to run all
possible combinations, trying each
of the remaining unknown cards and
reporting back how many times each
player wins, loses, or ties the
hand. If there are a large number of
unknowns you can do a
simulation¬-trying a hundred
thousand possibilities or so --
instead of going through all the
possibilities.
One common use
of this tool is for people who play
No-Limit Texas Hold’em. Put your
hole cards in, and the two cards of
your opponent (or leave your
opponents cards blank to simulate
they have a random hand) and press
go. It will tell you exactly what
your chances are if you go all-in
pre-flop. You can then decide if the
odds you are getting are worth the
risk. Experimentation with the
Showdown Calculator can be
invaluable for forming a strategy
for when you are low on chips in a
tournament and have to pick your
best shot for going all in.
Long-Term Playability
Quality
Artificial Intelligence is a key
component to the long-term
playability of skill based computer
software products. If the AI is
weak, games are too easily
overpowered by average and below
average players. The stronger more
adaptable the AI the more
challenging the software package
will be. If the software continues
to be challenging it continues to be
fun. A key factor in why games
become dull is that human players
learn simple ways to exploit
weaknesses, and the game ceases to
be a worthy challenge. For example
if you play a computer football game
and you discover a play that nets
you 30 yards every time you run it,
the game can become boring. That’s
where our advanced AI comes into
play. Our computer games
consistently challenge you because
they are always adapting to your
play, as a result you cannot bully
and win.
Artificial
Intelligence: Man vs. Machine
The industrial
revolution ushered in a new era of
human history where civilization
advanced by inventing machinery that
could do a job faster and with more
accuracy than its human counterpart.
Since that time machines have made
significant strides, first in
matching and exceeding human
physical labor and now trying to
match human intelligence.
In May 1997 the
World Chess Champion, Garry
Kasparov, a Grand Master and
considered the best chess player of
his time was defeated by Deep Blue;
a machine made of silicon, plastic,
and metal. The machine triumphed not
once, but twice. This highly
publicized match brought game theory
to the attention of the masses and
questioned whether man had usurped
his claim as the most intelligent
being with his own invention.
Three years
earlier, researchers at the
University of Alberta had studied
machine learning as it applied to
game theory by developing a checkers
playing program named Chinook.
Chinook became the best checkers
playing entity on the planet,
eventually winning the checkers
world championship by defeating
competitors in qualifying
tournaments and leaving a trail of
stunned human players in its wake.
Recognized by the Guinness Book of
World Records, the University team
wanted to build on this success and
apply their knowledge and
programming skills to other game
arenas. In the early stages of
development at the time of Chinook’s
checker victory was a program that
played Texas Hold'em Poker.
Play the Cards and
the Man
" [It] can be
unnerving for some of the better
human players, who often rely on
unbridled aggression to win. The
machines don't feel challenged as
humans do; they simply crunch more
numbers to decide the proper
response."
- New York
Times, July 10, 2003
The next
natural focus for the GAMES group
was opponent modeling. Neural
networks could predict to
satisfactory degree human responses
based on a set of stimuli; and so
Poki was built on the shoulders of
its predecessor, Loki. Though
deriving its name from humbling
beginnings (Poki was indicative of
how long the early versions would
take to run through modeling
scenarios), Poki soon proved itself
to be a significant step forward in
computer poker technology. The GAMES
group took its testing to the next
level by hosting a server that would
allow human opponents to come and
pit their skills against Poki with
play money. The more people that
came to try and beat the poker
robot, the more information Poki had
to work with and model against. Soon
Poki was taking all comers and
playing a solid, profitable poker
game. Now that Poki had proven
itself in full handed table games,
the researchers turned to another
area of poker research.
One-On-One
The movie A
Beautiful Mind introduced the public
to a concept long known by
mathematicians; Nobel laureate John
Nash’s concept of economic game
theory. Nash’s idea was applied to
heads-up poker to find an
approximation of an equilibrium
strategy—which is optimal play by
both players. This new program was
named Sparbot. Sparbot had a simpler
and more elegant approach to poker
than Poki; it would not play to win
but merely to not lose. In heads-up
poker, unlike other games of skill,
this can be a profitable strategy.
If your opponent plays well, a
Nash-optimal strategy will break
even over the long run; but if the
opponent makes any serious mistakes
(such as weak betting, or folding
too much), they will lose money.
Sparbot forces its opponent to
accept that breaking even may be
their best scenario.
Future of Artificial
Poker
“ The
artificial intelligence researchers
have moved one step closer to
creating an unbeatable computer
poker program. An account of their
most recent program, called PsOpti -
for pseudo-optimal poker program -
will receive the top paper award at
the world's premier AI meeting in
August.”
- National Sciences and Engineering
Research Council of Canada, June
2003
Now that poker
has exploded onto the stage of the
mainstream media, the research group
at the University of Alberta has
risen to the forefront of game
theory technology, and they show no
signs of slowing down. They have
recently been interviewed by the New
York Times, and had a feature piece
filmed by Discovery Channel Canada.
Edmonton has been thrust into the
limelight by their Games research,
and with the guidance of poker
theorist Darse Billings, the
development of poker game theory can
only grow in this "Vegas of the
North".
The newest
development by the University of
Alberta games group is Vexbot, which
is an AI system based completely on
opponent modeling. This is a radical
departure and very different from
the original rule-based Loki. It has
been successful thus far in proving
that opponent modeling is critical
when playing poker at a world class
level. Vexbot forces an opponent to
continually change strategies and
adapt their play, as it will attempt
to exploit any and all weakness or
predictability it finds in their
playing style. Players facing Vexbot
find themselves asking "how can I
win against myself?"
In the future,
poker enthusiasts can look forward
to a poker playing program that
incorporates all the best aspects of
Poki, Sparbot and Vexbot, resulting
in the ultimate training tool for
aspiring poker students dreaming of
victory at the final table.