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poker poker


Online games from chess and backgammon to 1st person shooters are rife with people who use computer assisted play or  keluaran togel singapura computer robots – even if there is no money at stake. With the proper program any player is able to play in a world championship level ruining the game for honest players. What makes online poker different, given that there are huge amounts of money at stake?

In this essay I will explain how I developed a poker bot and what I learnt from that experience. My decision is that though it will be likely to create a poker playing bot the threat from poker bots to the online poker player is very small to non profit.

For games such as Connect 4, Othello, chess and backgammon where all players have the same available information about the game state, the idea about how best to construct expert bots is well known. Deep search techniques, looking many moves ahead, are used for games like Othello and chess. Recently (10 years ago) it was discovered neural networks could be taught to play backgammon better than just about any human player. Games such as poker and bridge contain hidden information where the players can see their own hand but not that of the other players. The published theory behind writing expert computer bots for these incomplete information games is decades behind the complete information games and there are doubts techniques will be developed so that computers can play at expert or world championship level. At present the best techniques for these incomplete information games seem to involve some form of simulation and opponent modelling.

Anatomy of An Online Poker Bot

1) Data Gathering – observing the game state and history

2) Data Processing – using the data from the data gathered to determine whether to fold, call or raise.

3) Output – Pressing the suitable button on the poker room client.

My app was written in early 2004 with Microsoft .Net C++ and has been developed to play at one online room only.

1) Data Gathering

My bot gathered information about game state and history from internet poker tables by taking repeated screenshots and analysing the image. To begin with I just observed games, taking screenshots automatically so I could gather data on the positioning of the cards, chips and button. By specifying the color of a certain few pixels I was able to assemble all of this information about the state of the match.

Eventually I managed to assemble data from multiple poker tables (4 at a time) by repeatedly bringing each window to the foreground and taking a screenshot. From this screenshot I was able to determine my cards, board cards, button position, who was left at the hand, pot size and player bet sizes.

2) Data processing

This really is the component that eventually bought my poker bot project to an end, unable to develop a strong enough strategy to win consistently. I tried various rules based, neural net and simulation techniques. At best my bot was able to generate a very small profit at $1/2 and $2/$4 limit hold’em, but no where near the thousands of dollars a week I envisioned earning when I started the project. In the end it simply wasn’t worth my time for you to continue to put resources into developing my poker bot further.

3) Output

This is actually the easiest component to write. This involved programmatically moving the mouse pointer into the suitable screen co-ordinates and then sending a mouse down/mouse up command signalling a left-click. I did give consideration to adding the ability for the bot to use chat but never progressed that way.


Although you might run into a poker playing bot whilst playing online the chances are it plays very poorly. At any level of play you’re much more inclined to come across an expert human player than an expert computer player.