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One of the first studies of computer poker was done by Nicolas Findler
Findler77,Findler78. The variation of poker used in his
research was a simplified version of five-card draw poker. During the
years Findler's project was carried out, he developed a variety
poker-playing programs, each different in its structure and approach
to decision-making.
Virtually all of the early investigations into computer poker were done
by Findler and his associates. He would use the game of poker as a
model for a variety of studies which is now known as Artificial
Intelligence.
Findler was one of the first people to recognise the potential benefits
of research into poker, as a model for decision making under
uncertainty, but since his computer poker research was inspired by the
social sciences, his approaches were based significantly on the
psychological processes of human thought, rather than a mathematically
oriented analysis.
The poker variation addressed by Findler was not entirely realistic,
being a form of two-person Draw poker without any opening requirements
or ante, but it is still closer to real poker than any previously
existing mathematical model at the time.
Findler used a combination of a probabilistic assessment of hand
strength, with the collection of frequency data for opponent behaviour
to support the refinement of the models of opponent. The frequency data
was collected separately for each opponent and each round of play.
He considered that:
``In order to program a computer to play poker well it is necessary to
understand the cognitive processes employed when human beings play
poker. (The mathematical theory of games can only treat simplified
versions of the game).'' Findler's goal was not to create a world-class
poker-playing program and, as a result, none of his programs were very
strong players.
The algorithms developed also incorporated certain weak strategies,
such as betting in exact proportion to the strength of its hand (which
would convey too much information to an opponent).
Findler's research was not geared toward producing the strongest
possible poker program, but was focused on simulating the thought
processes of human players. While these may be interesting problems in
their own right, they impose severe limitations to the performance of a
program based on these ideas and is of limited usefulness to the future
development of a computer playing program. While the work Finder did was
worthwhile, the goal of producing high performance poker programs will
require not only different techniques, but a completely new, more
scientific and mathematical framework from which to build upon.
Next: Machine learning
Up: Previous Computer Science Studies
Previous: Previous Computer Science Studies
Jason R Carlton
2000-11-13