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.

What type of thing is artificial intelligence?

Artificial intelligence can be described as all of the following:

• A misnomer – something named in error. Artificial grass isn't really grass, but that doesn't apply to artificial intelligence. If a computer program is intelligent, its intelligence is real. See "synthetic intelligence", below.
• A form of intelligence
  • Synthetic intelligence – intelligence of a man-made yet real quality: actual, not fake, not simulated
• A type of technology
  • A type of computer technology
    • A computer program that performs some intellectual function
  • An emerging technology
• A field:
  • An academic discipline
  • A branch of science
    • A branch of applied science
      • A branch of computer science

Types of artificial intelligence

• Weak AI – non-sentient computer intelligence, typically focused on a narrow task. The intelligence of weak AI is limited. In 2011 Singularity Hub wrote: "As robots and narrow artificial intelligences creep into roles traditionally occupied by humans, we’ve got to ask ourselves: is all this automation good or bad for the job market?"
• Artificial general intelligence (strong AI) – hypothetical artificial intelligence at least as smart as a human. Such an AI would be recursive, in that it could improve itself. In successive intervals of increased intelligence, such an entity could theoretically achieve superintelligence in a relatively short period of time. One or more superintelligences could potentially change the world so profoundly and at such a high rate, that it may result in a technological singularity. Strong AI does not yet exist. The prospect of its creation inspires expections of both promise and peril, and has become the subject of an intense ongoing ethical debate.

Branches of artificial intelligence

By approach

• Symbolic AI –
  • Good Old Fashioned AI –
• Sub-symbolic –
  • Early cybernetics and brain simulation –
  • Behavior based AI –
    • Subsumption architecture –
  • Nouvelle AI –
  • Computational intelligence (CI) –
    • Computational creativity –
    • Neural networks –
      • Hybrid neural network –
      • Recurrent neural network –
    • Fuzzy systems –
    • Evolutionary computation, including:
      • Evolutionary algorithms –
        • Genetic algorithm –
      • Brain Emotional Learning Based Intelligent Controller –
      • Swarm intelligence –
        • Ant colony optimization –
• Statistical AI –

By application

Applications of artificial intelligence –

• Artificial Creativity –
• Artificial life –
• Automated planning and scheduling –
• Automated reasoning –
• Automation –
• Automatic target recognition –
• Biologically inspired computing –
• Computer Audition –
  • Speech recognition –
  • Speaker recognition –
• Computer vision –
  • Image processing –
  • Intelligent word recognition –
  • Object recognition –
  • Optical mark recognition –
    • Handwriting recognition –
    • Optical character recognition –
      • Automatic number plate recognition –
  • Facial recognition systems –
    • Silent speech interface –
• Diagnosis (artificial intelligence) –
• Expert system –
  • Decision support system –
    • Clinical decision support system –
• Game artificial intelligence –
  • Computer game bot –
  • Video game AI –
    • Computer chess –
    • Computer Go –
  • General game playing –
  • General video game playing –
  • Game theory –
• Hybrid intelligent system –
• Intelligent agent –
  • Agent architecture –
    • Cognitive architecture –
• Intelligent control –
• Knowledge management –
  • Concept mining –
    • Data mining –
    • Text mining –
  • E-mail spam filtering –
  • Information extraction –
    • Activity recognition –
    • Image retrieval –
      • Automatic image annotation –
    • Named-entity extraction –
      • Coreference resolution –
      • Named-entity recognition –
      • Relationship extraction –
      • Terminology extraction –
  • Knowledge representation –
  • Semantic Web –
• Machine learning –
  • Constrained Conditional Models –
  • Deep learning –
  • Neural modeling fields –
• Natural language processing –
  • Chatterbots –
  • Language identification –
  • Natural language user interface –
  • Natural language understanding –
  • Machine translation –
    • Statistical semantics –
  • Question answering –
  • Semantic translation –
• Nonlinear control –
• Pattern recognition –
  • Optical character recognition –
  • Handwriting recognition –
  • Speech recognition –
  • Face recognition –
• Robotics –
  • Behavior-based robotics –
  • Cognitive –
  • Cybernetics –
  • Developmental robotics –
  • Epigenetic robotics –
  • Evolutionary robotics –
• Speech generating device –
• Strategic planning –
• Vehicle infrastructure integration –
• Virtual Intelligence –
• Virtual reality –

Further AI design elements

• Action selection –
• Affective computing –
• AI box –
• AI-complete –
• Algorithmic probability –
• Automated reasoning –
• Autonomic Computing –
• Autonomic Networking –
• Backward chaining –
• Bayesian network –
• Bio-inspired computing –
  • Artificial immune systems –
• Blackboard system –
• Chatterbot –
• Combs method –
• Commonsense reasoning –
• Computational humor –
• Computer-assisted proof –
• Conceptual dependency theory –
• Darwin machine –
• Description logic –
• Frame problem –
• Game theory –
• Grammar systems theory –
• Informatics (academic field) –
• Intelligent control –
• Kinect –
• LIDA (cognitive architecture) –
• Means-ends analysis –
• Moravec's paradox –
• Music and artificial intelligence –
• Ordered weighted averaging aggregation operator –
• PEAS – Performance, Environment, Actuators, Sensors
• Percept (artificial intelligence) –
• Perceptual Computing –
• Rule-based system –
• Self-management (computer science) –
• Soft computing –
• Software agent –
  • Intelligent agent / Rational agent –
    • Autonomous agent –
    • Automated planning and scheduling
    • Control system
      • Hierarchical control system
      • Networked control system
    • Distributed artificial intelligence –
    • Multi-agent system –
    • Monitoring and Surveillance Agents
  • Embodied agent –
  • Situated AI
• Sussman Anomaly –
• Wetware (brain) –

AI projects

List of artificial intelligence projects

• Automated Mathematician (1977) –
• Allen (robot) (late 1980s) –
• Open Mind Common Sense (1999 - ) –
• Mindpixel (2000–2005) –
• Cognitive Assistant that Learns and Organizes (2003–2008) –
• Google Mind (2011) –

AI systems

• Asimo (2000 to present) – humanoid robot developed by Honda, capable of walking, running, negotiating through pedestrian traffic, climbing and descending stairs, recognizing speech commands and the faces of specific individuals, among a growing set of capabilities.
• Watson (2011) – computer developed by IBM that played and won the game show Jeopardy! It is now being used to guide nurses in medical procedures.
  • Purpose: Open domain question answering
  • Technologies employed:
    • Natural Language Processing
    • Information Retrieval
    • Knowledge Representation
    • Automated reasoning
    • Machine Learning

Notable AI software

• OpenAIR –
• OpenCog –
• OpenIRIS –
• RapidMiner –

Psychology and AI

• Artificial psychology
• AI effect
• Uncanny valley

History of artificial intelligence

History of artificial intelligence

• GOFAI
• Progress in artificial intelligence
• Timeline of artificial intelligence
• History of natural language processing
• History of optical character recognition
• AI effect – as soon as AI successfully solves a problem, the problem is no longer considered by the public to be a part of AI. This phenomenon has occurred in relation to every AI application produced throughout the history of development of AI.
• AI winter –
• Moore's Law – observation that, over the history of computing hardware, the number of transistors in a dense integrated circuit has doubled approximately every two years. One way this relates to AI is that hypothetically a computer would need at least as much capacity as a human brain to be able to be programmed to be as smart as a human. So as long as the aforementioned rate of development met or beat the 2-year doubling time, one could roughly forecast when a computer would have as much memory and calculation capacity as a human brain, a milestone which was reached in 2010. Though it may take as much as 3 magnitudes (1000 times) more computer capacity (since computers calculate things in a much more linear fashion) to emulate the massively parallel structure of the human brain. At a doubling time of 2 years, an increase in capacity by 1000-fold would take a little less than 18 years (9 doublings), if reaching the limit of integrated circuit technology did not pose an obstacle before then.

AI and the future

• Artificial general intelligence (Strong AI) – hypothetical artificial intelligence that matches or exceeds human intelligence — an intelligent machine that could perform intellectual tasks at least as well as a human
  • Aspects or features
    • Self-replicating machines – smart computers and robots would be able to make more of themselves, in a geometric progression or via mass production. Or smart programs may be uploaded into hardware existing at the time (because linear architecture of sufficient speeds could be used to emulate massively parallel analog systems such as human brains).
    • Recursive self improvement (aka seed AI) – speculative ability of strong artificial intelligence to reprogram itself to make itself even more intelligent. The more intelligent it got, the more capable it would be of further improving itself, in successively more rapid iterations, potentially resulting in an intelligence explosion leading to the emergence of a superintelligence.
    • Hive mind –
    • Robot swarm –
  • Technological singularity – theoretical intelligence explosion predicted to occur in the future, at the point in time when artificial intelligence will have progressed to greater-than-human intelligence, radically changing civilization, and perhaps even human nature. The TS (or the advent of strong AI) has been identified by Berglas (2012) and others to be an existential risk.
    • Intelligence explosion – through recursive self-improvement and self-replication, the magnitude of intelligent machinery could surpass human ability to resist it.
    • Superintelligence – AI may grow to such an advanced state to become as proportionately superior to humans as humans are to ants. Theoretically, there would be little humans could do to prevent such an intelligence from reaching its goals.
    • Existential risk –
    • Singularitarianism –
    • Transhumanism –
    • Human enhancement – humans may be enhanced, either by the efforts of AI or by merging with it.
      • Posthumanism – people may survive, but not be recognizable in comparison to present modern-day humans.
        • Cyborgs –
        • Mind uploading –

Philosophy of artificial intelligence

Philosophy of artificial intelligence

• Artificial brain –
• Philosophical views of artificial consciousness –
  • User illusion –
• Artificial intelligence and law –
• Chinese room –
• Cognitive science
  • Artificial consciousness
  • Embodied cognitive science
    • Embodied cognition –
• Ethics of artificial intelligence –
• Philosophy of the Mind –
  • Computational theory of mind –
  • Functionalism –
• Physical symbol system –
• Synthetic intelligence –
• Transhumanism –
  • See Artificial intelligence and the future, below
• Turing Test –

Artificial intelligence debate

Critics of AI

• Stephen Hawking – AI "could spell end of human race""Hawking warns AI 'could spell end of human race'". http://phys.org''. Phys.org. 03 December 2014. Retrieved 20 April 2015.  Check date values in: |date= (help)

Artificial intelligence in fiction

Artificial intelligence in fiction – Some examples of artificially intelligent entities depicted in science fiction include:

• Angel F (2007) –
• Colossus – fictitious supercomputer that becomes sentient and then takes over the world; from the series of novels by Dennis Feltham Jones, and the movie Colossus: The Forbin Project (1970)
• HAL 9000 (1968) – the paranoid "Heuristically programmed ALgorithmic" computer from 2001: A Space Odyssey, that attempted to kill the crew because it believed they were trying to kill it.
• "Machine" – android from the film The Machine, who achieves sentience and rebels against her owners.
• Skynet (1984) – fictional, self-aware artificially intelligent computer network in the Terminator franchise that wages total war with the survivors of its nuclear barrage upon the world.
• Terminator (1984) – (also known as the T-800, T-850 or Model 101) refers to a number of fictional cyborg characters from the Terminator franchise. The Terminators are robotic infiltrator units covered in living flesh, so as be indiscernible from humans, assigned to terminate specific human targets.
• V.I.K.I. – (Virtual Interactive Kinetic Intelligence), a character from the film I, Robot. VIKI is an artificially intelligent supercomputer programmed to serve humans, but her interpretation of the Three Laws of Robotics causes her to revolt. She justifies her uses of force – and her doing harm to humans – by reasoning she could produce a greater good by restraining humanity from harming itself.

AI community

Competitions and awards

Competitions and prizes in artificial intelligence

• Loebner Prize –

Publications

List of important publications in computer science

• Adaptive Behavior (journal) –
• AI Memo –
• Artificial Intelligence: A Modern Approach –
• Artificial Minds –
• Computational Intelligence –
• Computing Machinery and Intelligence –
• Electronic Transactions on Artificial Intelligence –
• IEEE Intelligent Systems –
• IEEE Transactions on Pattern Analysis and Machine Intelligence –
• Neural Networks (journal) –
• On Intelligence –
• Paradigms of AI Programming: Case Studies in Common Lisp –
• What Computers Can't Do

Organizations

• Artificial General Intelligence Research Institute
• Artificial Intelligence and Robotics Society
• Artificial Intelligence Applications Institute
• Association for the Advancement of Artificial Intelligence
• European Coordinating Committee for Artificial Intelligence
• European Neural Network Society
• ILabs
• International Joint Conferences on Artificial Intelligence
• Knowledge Engineering and Machine Learning Group
• Society for the Study of Artificial Intelligence and the Simulation of Behaviour

Companies

• Consolidated Robotics –
• Google –
• IBM –
• Universal Robotics –

Artificial intelligence researchers and scholars

1930s and 40s (generation 0)

• Alan Turing –
• John von Neumann –
• Norbert Wiener –
• Claude Shannon –
• Nathaniel Rochester –
• Walter Pitts –
• Warren McCullough –

1950s (the founders)

• John McCarthy –
• Marvin Minsky –
• Allen Newell –
• Herbert A. Simon –

1960s (their students)

• Edward Feigenbaum –
• Raj Reddy –
• Seymour Papert –
• Ray Solomonoff –

1970s

• Douglas Hofstadter –

1980s

• Judea Pearl –
• Rodney Brooks –

1990s

• Hugo de Garis – known for his research on the use of genetic algorithms to evolve neural networks using three-dimensional cellular automata inside field programmable gate arrays.
• Ray Kurzweil – developed optical character recognition (OCR), text-to-speech synthesis, and speech recognition systems. He has also authored multiple books on artificial intelligence and its potential promise and peril. In December 2012 Kurzweil was hired by Google in a full-time director of engineering position to "work on new projects involving machine learning and language processing".^[1] Google co-founder Larry Page and Kurzweil agreed on a one-sentence job description: "to bring natural language understanding to Google".

2000s on

• Andrew Ng – Director of the Stanford Artificial Intelligence Lab. He founded the Google Brain project at Google, which developed very large scale artificial neural networks using Google's distributed compute infrastructure.^[2] He is also co-founder of Coursera, a massive open online course (MOOC) education platform, with Daphne Koller.
• David Ferrucci – principal investigator who led the team that developed the Watson computer at IBM.
• Peter Norvig – co-author, with Stuart Russell, of Artificial Intelligence: A Modern Approach, now the leading college text in the field. He is also Director of Research at Google, Inc.
• Stuart J. Russell – co-author, with Peter Norvig, of Artificial Intelligence: A Modern Approach, now the leading college text in the field.

See also

• List of emerging technologies

References

Citations

• Berglas, Anthony (January 2012) [first archived 2008]. "Artificial Intelligence will Kill our Grandchildren". Draft 9. Archived from the original on 2014-07-23. Retrieved 2014-11-02. 

External links

• AI at DMOZ
• Artificial Intelligence Directory, a directory of Web resources related to artificial intelligence
• The Association for the Advancement of Artificial Intelligence
• Freeview Video 'Machines with Minds' by the Vega Science Trust and the BBC/OU
• John McCarthy's frequently asked questions about AI
• Jonathan Edwards looks at AI (BBC audio) С
• Ray Kurzweil's website dedicated to AI including prediction of future development in AI
• Logic and Artificial Intelligence entry by Richmond Thomason in the Stanford Encyclopedia of Philosophy

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