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Game playing was an area of research in AI from its inception. One of the first examples of AI is the computerized game of Nim made in 1951 and published in 1952. Despite being advanced technology in the year it was made, 20 years before Pong, the game took the form of a relatively small box and was able to regularly win games even against highly skilled players of the game. [1]
The game ends if the AI succeeds in converting all the matter in the universe into paperclips. Both the title of the game and its overall concept draw from the paperclip maximizer thought experiment first described by Swedish philosopher Nick Bostrom in 2003, a concept later discussed by multiple commentators.
Computer Go is the field of artificial intelligence (AI) dedicated to creating a computer program that plays the traditional board game Go.The field is sharply divided into two eras.
AI Dungeon is a text adventure game that uses artificial intelligence to generate random storylines in response to player-submitted stimuli. [1] [2] [3] [4]In the game, players are prompted to choose a setting for their adventure (e.g. fantasy, mystery, apocalyptic, cyberpunk, zombies), [5] [6] followed by other options relevant to the setting (such as character class for fantasy settings).
General game playing (GGP) is the design of artificial intelligence programs to be able to play more than one game successfully. [1] [2] [3] For many games like chess, computers are programmed to play these games using a specially designed algorithm, which cannot be transferred to another context.
Chess is a turn-based strategy game that is considered a difficult AI problem due to the computational complexity of its board space. Similar strategy games are often solved with some form of a Minimax Tree Search. These types of AI agents have been known to beat professional human players, such as the historic 1997 Deep Blue versus Garry ...
Many open world or survival games procedurally create a game world from a random seed or one provided by the player, so that each playthrough is different. These generation systems create numerous pixel- or voxel-based biomes with distribution of resources, objects, and creatures. The player frequently has the ability to adjust some of the ...
Decommissioned AlphaGo backend rack. Go is considered much more difficult for computers to win than other games such as chess, because its strategic and aesthetic nature makes it hard to directly construct an evaluation function, and its much larger branching factor makes it prohibitively difficult to use traditional AI methods such as alpha–beta pruning, tree traversal and heuristic search.