It’s that time of the year again… the word spreads, I download it, and my nights fly by. It’s time for the new Google AI Challenge: http://aichallenge.org/ ! This time we will be writing multi-agent systems, as we program cyber-ant-colonies fighting against each other for bread crumbs.

Some computer games offer the possibility to extend their Artificial Intelligence with external scripts, or are explicitly designed to be played by bots. Such games are a great resource to develop, test, and teach AI algorithms. I have been looking for a list of this kind of games, but could find very little information, often [...]

Perhaps inspired by the victory of the artificial brain Watson against humanity, the New York Times is offering today an interactive feature that allows to play a series of Rock-Paper-Scissors games against the computer. The prediction algorithm seems to be a simple Bayesian estimator like the one I implemented for the Karate A.I. game. The [...]

I never got the chance to show a working agent based on the Bayesian estimator for the enemy position in the PacMan capture-the-flag game. In the previous PacMan post, I wrote about merging a model of agent movements with the noisy measurements returned by the game to track the enemy agents across the maze. Clearly, [...]

The Computer Science of the University of Waterloo is organizing its second Google AI Challenge. The challenge is a competition between computer programs that control the artificial intelligence of the players in a video game. This time, the game is set in space, and features a symmetric configuration of planets, each containing a fleet of [...]

As another scientific Python course is approaching, I’ve been brushing up my PacMan skills. I decided to give a try to a strategy I had been thinking on, which relies upon having a good estimate of the enemy’s position. I should remind the reader that in the PacMan capture-the-flag game, one team does not know [...]

At the beginning of September I’ve been invited to teach at a summer school about scientific programming. The whole experience has been really rewarding, but it was the student’s project that got me going: we had the students write artificial intelligence algorithms for the agents of a PacMan-like game, and organized a tournament for them [...]

In the previous two posts I showed how to make use of decision theory to write a game AI that forms a model of its opponent and adapts its strategy accordingly. The AI could be improved in several ways: The most obvious improvement would be to build a better model of the opponent. In the [...]

In the last post I discussed how it is possible to program a game Artificial Intelligence to exploit a player’s unconscious biases using a simple mathematical model. In the karate game above, the AI uses that model in order to do the largest amount of damage. Give [...]

I regularly read about people complaining that AI in games should be improved. I definitely agree with them, but here’s a argument why pushing it to the limits might not be such a good idea: computers can easily discover and exploit our unconscious biases. Magic? ESP? More like a simple application of decision theory. In [...]