Mizar chess engine

Games are ideal domain for exploring the capabilities of computational intelligence. The rules are fixed, the scope of the problem is constrained, and the interactions of player are well defined.

Historically, games have been a popular choice for demonstrating new research ideas in artificial intelligence. Indeed, one of the early goals of AI was to build a program capable of defeating the human world chess champion in a match.

Computer-games research started in 1950 when Cloude Shannon, one of the luminaries in computing science history, published his seminal paper that laid out the framework for building high-performance game playing programs.

In the half century years since Shannon’s papers, enormous progress has been made and chess isn’t the only board-game researched. In the 1980s David Levy creates the Computer Olympiad: a multi-games event taking place every year in which computer programs compete against each other. The majority of the games are board games but other games such as Bridge take place as well. The Olympiad was originally held in either London or Maastricht, lately however, cities from around the world have hosted the Olympiad.

Game artificial intelligence

Today techniques of Game artificial intelligence are also used in computer and video games to produce the illusion of intelligence. The techniques used typically draw upon existing methods from the field of artificial intelligence. Game AI/heuristic algorithms are used in a wide variety of quite disparate fields inside a game. The most obvious is in the control of any non-player characters (NPCs) in the game, although scripting is currently the most common means of control. Pathfinding is another common use for AI, widely seen in real-time strategy games. Pathfinding is the method for determining how to get an NPC from one point on a map to another, taking into consideration the terrain, obstacles and possibly “fog of war”. Game AI is also involved with dynamic game difficulty balancing, which consists in adjusting the difficulty in a video game in real-time based on the player’s ability.

The concept of emergent AI has recently been explored in games such as Creatures, Black & White and Nintendogs and toys such as Tamagotchi. The “pets” in these games are able to “learn” from actions taken by the player and their behavior is modified accordingly. While these choices are taken from a limited pool, it does often give the desired illusion of an intelligence on the other side of the screen.

Since game AI is centered on appearance of intelligence and good gameplay, its approach is very different from that of traditional AI; hacks and cheats are acceptable and, in many cases, the computer abilities must be toned down to give human players a sense of fairness. This, for example, is true in first-person shooter games, where NPC’s otherwise perfect aiming would be beyond human skill.

Cheating AI are a well-known aspect of Sid Meyer’s Civilization series; in those games, the player must build his empire from scratch, while the computer’s empire recieves additional units at no cost and is freed from most resource restrictions.

Here you will find informations, papers and source codes:

Games Artificial Intelligence Directory