Outline of artificial intelligence The following outline is provided as an overview of and topical guide to artificial intelligence: Artificial intelligence (AI) – branch of computer science that deals with intelligent behavior, learning, and adaptation in machines. Research in AI is concerned with producing machines to automate tasks requiring intelligent behavior. Branches of artificial intelligence[edit] Some applications of artificial intelligence[edit] Philosophy of artificial intelligence[edit] Philosophy of artificial intelligence Artificial intelligence and the future[edit] Strong AI – hypothetical artificial intelligence that matches or exceeds human intelligence — the intelligence of a machine that could successfully perform any intellectual task that a human being can. History of artificial intelligence[edit] Main article: History of artificial intelligence Artificial intelligence in fiction[edit] Main article: Artificial intelligence in fiction Psychology and AI[edit] Concepts in artificial intelligence[edit] 1970s[edit]
Araucaria (software) The user interface is composed of a main window (diagramming), a schemes editor and the AraucariaDB online interface. While Araucaria helps identify the structure of an argument, it provides freedom of analysis resources. The scheme editor allows the user to create argumentation schemes, group them together and save them into a scheme set file. The AraucariaDB Online Repository can be browsed to retrieve specific arguments to fit a diagram. Because it is based on XML, a standard widely used by developers, AML content can be accessed through other software that support XML.
Artificial intelligence AI research is highly technical and specialized, and is deeply divided into subfields that often fail to communicate with each other.[5] Some of the division is due to social and cultural factors: subfields have grown up around particular institutions and the work of individual researchers. AI research is also divided by several technical issues. Some subfields focus on the solution of specific problems. The central problems (or goals) of AI research include reasoning, knowledge, planning, learning, natural language processing (communication), perception and the ability to move and manipulate objects.[6] General intelligence is still among the field's long-term goals.[7] Currently popular approaches include statistical methods, computational intelligence and traditional symbolic AI. The field was founded on the claim that a central property of humans, intelligence—the sapience of Homo sapiens—"can be so precisely described that a machine can be made to simulate it History[edit]
Argument map Visual representation of the structure of an argument Argument maps are commonly used in the context of teaching and applying critical thinking.[2] The purpose of mapping is to uncover the logical structure of arguments, identify unstated assumptions, evaluate the support an argument offers for a conclusion, and aid understanding of debates. Argument maps are often designed to support deliberation of issues, ideas and arguments in wicked problems.[3] A number of different kinds of argument maps have been proposed but the most common, which Chris Reed and Glenn Rowe called the standard diagram,[5] consists of a tree structure with each of the reasons leading to the conclusion. There is no consensus as to whether the conclusion should be at the top of the tree with the reasons leading up to it or whether it should be at the bottom with the reasons leading down to it.[5] Another variation diagrams an argument from left to right.[6] According to Douglas N. [edit] Diagramming written text
artifical intelligence diagram Artificial intelligence in video games Artificial intelligence (AI) in video games refers to the computational systems that control non-player characters (NPCs), generate dynamic game behavior, or simulate strategic decision-making. In practice, the term covers a broad range of techniques drawn from computer science, control theory, and robotics rather than “true” artificial intelligence. Moreover, academic AI—aimed at developing autonomous reasoning or learning—is distinct from game AI, whose goal is to deliver engaging, believable, and efficient behavior for players. In general, game AI does not, as might be thought and sometimes is depicted to be the case, mean a realization of an artificial person corresponding to an NPC in the manner of the Turing test or an artificial general intelligence. Some commentators in the video game industry have claimed that advances in game AI have transformed how players interact with digital systems more broadly. However, such claims remain disputed. In computer simulations of board games
IMG 5463 As a service Service model[edit] See cloud computing service models for more information. Examples[edit] Examples include: References[edit] ^ Robin Hastings, Making the Most of the Cloud: How to Choose and Implement the Best Services (2013), p. 3.^ I. Category:Artificial intelligence From Wikipedia, the free encyclopedia Subcategories This category has the following 32 subcategories, out of 32 total. Pages in category "Artificial intelligence" The following 200 pages are in this category, out of 256 total. (previous 200) (next 200)(previous 200) (next 200)
Browser extension A browser extension is a small software module for customizing a web browser. Browsers typically allow a variety of extensions, including user interface modifications, ad blocking, and cookie management. History[edit] API conformity[edit] In 2015, a community working group formed under the W3C to create a single standard application programming interface (API) for browser extensions.[3] While that goal is unlikely to be achieved,[4] the majority of browsers already use the same or very similar APIs due to the popularity of Google Chrome. Chrome was the first browser with an extension API based solely on HTML, CSS, and JavaScript. With its own market share in decline, Mozilla also decided to conform. Unwanted behavior[edit] There have also been cases of applications installing browser extensions in a sneaky manner, while making it hard for the user to uninstall the unwanted extension.[25] References[edit] External links[edit] Official extension stores for Chrome, Safari, Firefox, Edge, Opera
FLI - Future of Life Institute (If you have questions about this letter, please contact tegmark@mit.edu) Artificial intelligence (AI) research has explored a variety of problems and approaches since its inception, but for the last 20 years or so has been focused on the problems surrounding the construction of intelligent agents - systems that perceive and act in some environment. In this context, "intelligence" is related to statistical and economic notions of rationality - colloquially, the ability to make good decisions, plans, or inferences. The adoption of probabilistic and decision-theoretic representations and statistical learning methods has led to a large degree of integration and cross-fertilization among AI, machine learning, statistics, control theory, neuroscience, and other fields. The progress in AI research makes it timely to focus research not only on making AI more capable, but also on maximizing the societal benefit of AI. List of signatories
Automated reasoning Automated reasoning is an area of computer science and mathematical logic dedicated to understanding different aspects of reasoning. The study of automated reasoning helps produce computer programs that allows computers to reason completely, or nearly completely, automatically. Although automated reasoning is considered a sub-field of artificial intelligence, it also has connections with theoretical computer science, and even philosophy. The most developed subareas of automated reasoning are automated theorem proving (and the less automated but more pragmatic subfield of interactive theorem proving) and automated proof checking (viewed as guaranteed correct reasoning under fixed assumptions). Other important topics include reasoning under uncertainty and non-monotonic reasoning. Tools and techniques of automated reasoning include the classical logics and calculi, fuzzy logic, Bayesian inference, reasoning with maximal entropy and a large number of less formal ad hoc techniques.