Artificial Intelligence in Video Games

Abstract

While the relationship between artificial intelligence (AI) and games far exceeds the parameters that a short review can even sketch out, I hope to propose a series of representational, historical, aesthetic, technical, experimental, and processual ways to approach the intersection between these two terms.Representations of AI and intelligent robots have been common throughout video game history, ranging from nonplayer to player characters. Some representations of AI antagonists include AM in I Have No Mouth, and I Must Scream (Cyberdreams and the Dreamers Guild, 1995), GLaDOS in Portal (Valve, 2007), and P03 in Inscryption (Daniel Mullins Games 2021). Depictions of helpful nonplayer AI familiars include Rush in Mega Man 3 (Capcom, 1990), Claptrap in Borderlands (Gearbox Software, 2009), and Nick Valentine in Fallout 4 (Bethesda Game Studios, 2015). Another important category comprises AI player-characters whom a player controls or roleplays as but that do not depend on actual AI systems, including Mega Man throughout the Mega Man series (Capcom, 1987–), the unnamed android of The Talos Principle (Croteam, 2014), and SAM in Observation (No Code, 2019). The centrality of science fiction as a popular narrative genre in video games—a medium that emerged during the Cold War when speculative narratives were assuming a more central form within popular culture—might account for the prevalence of AI characters in games.Unlike literature, film, or television series, however, the history of AI in video games exceeds representation. The earliest history of AI includes uses of games to test AI programs. Already in the late 1940s, mathematicians Alan Turing and Claude Shannon both used chess-playing programs as a theoretical route into the problem of how a computer could think. Some of the earliest examples of video games, such as Tennis for Two (William Higinbotham, 1958), Spacewar! (Steve Russell, 1962), and Pong (Atari, 1972), were two-player games in which the challenge derived from the other player, thereby eliminating the need for AI. The development of AI in popular video games initiated an era of single-player engagements, starting with games such as Computer Space (Syzygy Engineering, 1971) and Space Invaders (Taito, 1978). Enemy behaviors in such single-player games, which depend on character-based scripting and pathfinding algorithms, are more basic than the supervised and unsupervised learning of later neural networks. Historically, developers have often spent more resources on graphics than AI systems in order to appeal to consumers through visual delights. Even so, AI has become more important to video games in the early twenty-first century.Though the larger topic of AI uses within video game development exceeds the scope of a short review, it is helpful to think through the aesthetic effects that AI can have in games at the intersection of interactive art and computer science. For example, as I have argued elsewhere (Jagoda 2020), difficulty is an aesthetic dimension of interactive games. Some games use AI to achieve adaptive difficulty. By contrast to variable difficulty, which allows a player to choose a difficulty setting that might include easy (or story), normal, or difficult modes, adaptive difficulty responds to a player’s performance in real time. Crash Bandicoot 2 (Naughty Dog, 1997) was one of the earliest video games to experiment with dynamic difficulty, providing a player who failed often with added checkpoints or stronger power-ups. Another example comes with the practice of “rubberbanding” in multiplayer video games in which a game increases or decreases difficulties based on players’ real-time performances, as with the infamous “spiny” or “blue” shell that targets the first-place racer in all games in the Mario Kart series (starting with Mario Kart 64 [Nintendo EAD, 1996]) to maintain parity.Other games use more sophisticated AI systems to produce emergent gameplay, which includes adaptive difficulty but als