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. Before 2015, the programs of the era were weak. The best efforts of the 1980s and 1990s produced only AIs that could be defeated by beginners, and AIs of the early 2000s were intermediate level at best. Professionals could defeat these programs even given handicaps of 10+ stones in favor of the AI. Many of the algorithms such as alpha-beta minimax that performed well as AIs for checkers and chess fell apart on Go's 19x19 board, as there were too many branching possibilities to consider. Creation of a human professional quality program with the techniques and hardware of the time was out of reach. Some AI researchers speculated that the problem was unsolvable without creation of human-like AI.
A zero-player game or no-player game is a simulation game that has no sentient players.
A game programmer is a software engineer, programmer, or computer scientist who primarily develops codebases for video games or related software, such as game development tools. Game programming has many specialized disciplines, all of which fall under the umbrella term of "game programmer". A game programmer should not be confused with a game designer, who works on game design.
In artificial intelligence, symbolic artificial intelligence is the term for the collection of all methods in artificial intelligence research that are based on high-level symbolic (human-readable) representations of problems, logic and search. Symbolic AI used tools such as logic programming, production rules, semantic nets and frames, and it developed applications such as knowledge-based systems, symbolic mathematics, automated theorem provers, ontologies, the semantic web, and automated planning and scheduling systems. The Symbolic AI paradigm led to seminal ideas in search, symbolic programming languages, agents, multi-agent systems, the semantic web, and the strengths and limitations of formal knowledge and reasoning systems.
Omega is a video game developed and published by Origin Systems in 1989. It was directed by Stuart B. Marks.
A computer poker player is a computer program designed to play the game of poker, against human opponents or other computer opponents. It is commonly referred to as pokerbot or just simply bot. As of 2019, computers can beat any human player in poker.
Interactive storytelling is a form of digital entertainment in which the storyline is not predetermined. The author creates the setting, characters, and situation which the narrative must address, but the user experiences a unique story based on their interactions with the story world. The architecture of an interactive storytelling program includes a drama manager, user model, and agent model to control, respectively, aspects of narrative production, player uniqueness, and character knowledge and behavior. Together, these systems generate characters that act "human," alter the world in real-time reactions to the player, and ensure that new narrative events unfold comprehensibly.
Roger Carl Schank was an American artificial intelligence theorist, cognitive psychologist, learning scientist, educational reformer, and entrepreneur. Beginning in the late 1960s, he pioneered conceptual dependency theory and case-based reasoning, both of which challenged cognitivist views of memory and reasoning. He began his career teaching at Yale University and Stanford University. In 1989, Schank was granted $30 million in a ten-year commitment to his research and development by Andersen Consulting, through which he founded the Institute for the Learning Sciences (ILS) at Northwestern University in Chicago.
In video games, artificial intelligence (AI) is used to generate responsive, adaptive or intelligent behaviors primarily in non-playable characters (NPCs) similar to human-like intelligence. Artificial intelligence has been an integral part of video games since their inception in the 1950s. AI in video games is a distinct subfield and differs from academic AI. It serves to improve the game-player experience rather than machine learning or decision making. During the golden age of arcade video games the idea of AI opponents was largely popularized in the form of graduated difficulty levels, distinct movement patterns, and in-game events dependent on the player's input. Modern games often implement existing techniques such as pathfinding and decision trees to guide the actions of NPCs. AI is often used in mechanisms which are not immediately visible to the user, such as data mining and procedural-content generation.
Façade is an artificial intelligence-based interactive story created in 2005 by Michael Mateas and Andrew Stern. Upon release, the game received attention from mainstream news publications for its innovative design, and prompted speculation about the potential use of artificial intelligence in video games. Following release, Façade has received a generally positive reception, with praise directed at its technical innovation and wide cultural appeal, particularly in online streaming, and mixed views directed to the verisimilitude of its representation of interpersonal interaction.
Action selection is a way of characterizing the most basic problem of intelligent systems: what to do next. In artificial intelligence and computational cognitive science, "the action selection problem" is typically associated with intelligent agents and animats—artificial systems that exhibit complex behaviour in an agent environment. The term is also sometimes used in ethology or animal behavior.
General game playing (GGP) is the design of artificial intelligence programs to be able to play more than one game successfully. For many games like chess, computers are programmed to play these games using a specially designed algorithm, which cannot be transferred to another context. For instance, a chess-playing computer program cannot play checkers. General game playing is considered as a necessary milestone on the way to artificial general intelligence.
Anti-computer tactics are methods used by humans to try to beat computer opponents at various games, most typically board games such as chess and Arimaa. They are most associated with competitions against computer AIs that are playing to their utmost to win, rather than AIs merely programmed to be an interesting challenge that can be given intentional weaknesses and quirks by the programmer. Such tactics are most associated with the era when AIs searched a game tree with an evaluation function looking for promising moves, often with Alpha–beta pruning or other minimax algorithms used to narrow the search. Against such algorithms, a common tactic is to play conservatively aiming for a long-term advantage. The theory is that this advantage will manifest slowly enough that the computer is unable to notice in its search, and the computer won't play around the threat correctly. This may result in, for example, a subtle advantage that eventually turns into a winning chess endgame with a passed pawn.
Magic: The Gathering – Duels of the Planeswalkers is a video game based on the popular collectible card game of the same name, published by Wizards of the Coast. It was released on June 17, 2009.
In the field of artificial intelligence (AI) design, AI capability control proposals, also referred to as AI confinement, aim to increase our ability to monitor and control the behavior of AI systems, including proposed artificial general intelligences (AGIs), in order to reduce the danger they might pose if misaligned. However, capability control becomes less effective as agents become more intelligent and their ability to exploit flaws in human control systems increases, potentially resulting in an existential risk from AGI. Therefore, the Oxford philosopher Nick Bostrom and others recommend capability control methods only as a supplement to alignment methods.
DeepMind Technologies Limited, doing business as Google DeepMind, is a British-American artificial intelligence research laboratory which serves as a subsidiary of Google. Founded in the UK in 2010, it was acquired by Google in 2014 and merged with Google AI's Google Brain division to become Google DeepMind in April 2023. The company is based in London, with research centres in Canada, France, Germany, and the United States.
In artificial intelligence, a behavior selection algorithm, or action selection algorithm, is an algorithm that selects appropriate behaviors or actions for one or more intelligent agents. In game artificial intelligence, it selects behaviors or actions for one or more non-player characters. Common behavior selection algorithms include:
DeepStack is an artificial intelligence computer program designed to play two-player poker, specifically heads up no-limit Texas hold 'em. It is the first computer program to outplay human professionals in this game.
