Poker Academy: Texas Holdem Software
Superior to any other product of its kind on the market, Poker Academy adjusts to each individual player using
advanced AI. This means staying power. Poker Academy's AI adds to the long-term playability of the game so users
won't get bored by figuring out simple easy-to-beat computer opponents. This also means Poker Academy will be
the most popular game in its class because it truly helps people become better players by teaching them how to
bluff, semi-bluff, and use math and odds to WIN.
Poker Academy Full Version
Poker Academy Software Features :
- Poker Academy's artificial intelligence is the most advanced
Poker AI in the world. Our advanced AI has computer opponents
that will challenge any level of player.
- Advanced research and analysis tools are available to help
find holes in your game and investigate sophisticated strategies.
|Game Price :
||Windows 7, Vista, 2000, XP
|| Pentium 133
Sound card recommended
32 MB RAM
15 MB of available hard drive space
SVGA 800x600 high color
|About Poker Academy: Texas Holdem Software
Learn by Playing
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.
Learn by Playing
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.
Learn by Playing
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.
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."
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.
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."
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.