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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).
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 follows the rise of a self-improving AI tasked with maximizing paperclip production, [6] a directive it takes to the logical extreme. An activity log records the player’s accomplishments while giving glimpses into the AI's occasionally unsettling thoughts. [7] [failed verification] All game interaction is done through pressing buttons.
Roguelikes, and games based on the roguelike concepts, allow the development of complex gameplay without having to spend excessive time in creating a game's world. [7] 1978's Maze Craze for the Atari VCS used an algorithm to generate a random, top-down maze for each game. [8] Some games used pseudorandom number generators.
Generative AI features have been integrated into a variety of existing commercially available products such as Microsoft Office (Microsoft Copilot), [85] Google Photos, [86] and the Adobe Suite (Adobe Firefly). [87] Many generative AI models are also available as open-source software, including Stable Diffusion and the LLaMA [88] language model.
Other games procedurally generate other aspects of gameplay, such as the weapons in Borderlands which have randomized stats and configurations. [3] This is a list of video games that use procedural generation as a core aspect of gameplay. Games that use procedural generation solely during development as part of asset creation are not included.
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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.