In video games, artificial intelligence is used to generate intelligent behaviors primarily in non-player characters (NPCs), often simulating human-like intelligence. The techniques used typically draw upon existing methods from the field of artificial intelligence (AI). However, the term game AI is often used to refer to a broad set of algorithms that also include techniques from control theory, robotics, computer graphics and computer science in general. <\/p>\n
Since game AI for NPCs is centered on appearance of intelligence and good gameplay within environment restrictions, its approach is very different from that of traditional AI; workarounds 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 NPCs' otherwise perfect aiming would be beyond human skill. <\/p>\n
Game playing was an area of research in AI from its inception. One of the first examples of AI is the computerised 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] In 1951, using the Ferranti Mark 1 machine of the University of Manchester, Christopher Strachey wrote a checkers program and Dietrich Prinz wrote one for chess.[2] These were among the first computer programs ever written. Arthur Samuel's checkers program, developed in the middle 50s and early 60s, eventually achieved sufficient skill to challenge a respectable amateur.[3] Work on checkers and chess would culminate in the defeat of Garry Kasparov by IBM's Deep Blue computer in 1997.[4] The first video games developed in the 1960s and early 1970s, like Spacewar!, Pong, and Gotcha (1973), were games implemented on discrete logic and strictly based on the competition of two players, without AI. <\/p>\n
Games that featured a single player mode with enemies started appearing in the 1970s. The first notable ones for the arcade appeared in 1974: the Taito game Speed Race (racing video game) and the Atari games Qwak (duck hunting light gun shooter) and Pursuit (fighter aircraft dogfighting simulator). Two text-based computer games from 1972, Hunt the Wumpus and Star Trek, also had enemies. Enemy movement was based on stored patterns. The incorporation of microprocessors would allow more computation and random elements overlaid into movement patterns. <\/p>\n
It was during the golden age of video arcade games that the idea of AI opponents was largely popularized, due to the success of Space Invaders (1978), which sported an increasing difficulty level, distinct movement patterns, and in-game events dependent on hash functions based on the player's input. Galaxian (1979) added more complex and varied enemy movements, including maneuvers by individual enemies who break out of formation. Pac-Man (1980) introduced AI patterns to maze games, with the added quirk of different personalities for each enemy. Karate Champ (1984) later introduced AI patterns to fighting games, although the poor AI prompted the release of a second version. First Queen (1988) was a tactical action RPG which featured characters that can be controlled by the computer's AI in following the leader.[5][6] The role-playing video game Dragon Quest IV (1990) introduced a \"Tactics\" system, where the user can adjust the AI routines of non-player characters during battle, a concept later introduced to the action role-playing game genre by Secret of Mana (1993). <\/p>\n
Games like Madden Football, Earl Weaver Baseball and Tony La Russa Baseball all based their AI on an attempt to duplicate on the computer the coaching or managerial style of the selected celebrity. Madden, Weaver and La Russa all did extensive work with these game development teams to maximize the accuracy of the games.[citation needed] Later sports titles allowed users to \"tune\" variables in the AI to produce a player-defined managerial or coaching strategy. <\/p>\n
The emergence of new game genres in the 1990s prompted the use of formal AI tools like finite state machines. Real-time strategy games taxed the AI with many objects, incomplete information, pathfinding problems, real-time decisions and economic planning, among other things.[7] The first games of the genre had notorious problems. Herzog Zwei (1989), for example, had almost broken pathfinding and very basic three-state state machines for unit control, and Dune II (1992) attacked the players' base in a beeline and used numerous cheats.[8] Later games in the genre exhibited more sophisticated AI. <\/p>\n
Later games have used bottom-up AI methods, such as the emergent behaviour and evaluation of player actions in games like Creatures or Black & White. Faade (interactive story) was released in 2005 and used interactive multiple way dialogs and AI as the main aspect of game. <\/p>\n
Games have provided an environment for developing artificial intelligence with potential applications beyond gameplay. Examples include Watson, a Jeopardy-playing computer; and the RoboCup tournament, where robots are trained to compete in soccer.[9] <\/p>\n
Purists complain that the \"AI\" in the term \"game AI\" overstates its worth, as game AI is not about intelligence, and shares few of the objectives of the academic field of AI. Whereas \"real\" AI addresses fields of machine learning, decision making based on arbitrary data input, and even the ultimate goal of strong AI that can reason, \"game AI\" often consists of a half-dozen rules of thumb, or heuristics, that are just enough to give a good gameplay experience.[citation needed] Historically, academic game-AI projects have been relatively separate from commercial products because the academic approaches tended to be simple and non-scalable. Commercial game AI has developed its own set of tools, which have been sufficient to give good performance in many cases.[10] <\/p>\n
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