AI Ed‎ > ‎


  1.  Definition of AI as the study of intelligent agents:
  2. Jump up^ Russell & Norvig 2009, p. 2.
  3. Jump up^ Hofstadter (1980, p. 601)
  4. Jump up^ Schank, Roger C. (1991). "Where's the AI". AI magazine. Vol. 12 no. 4. p. 38.
  5. Jump up^ Russell & Norvig 2009.
  6. Jump up to:a b "AlphaGo – Google DeepMind"Archived from the original on 10 March 2016.
  7. Jump up to:a b Optimism of early AI:
  8. Jump up to:a b c Boom of the 1980s: rise of expert systemsFifth Generation ProjectAlveyMCCSCI:
  9. Jump up to:a b First AI WinterMansfield AmendmentLighthill report
  10. Jump up to:a b Second AI winter:
  11. Jump up to:a b c AI becomes hugely successful in the early 21st century
  12. Jump up to:a b Pamela McCorduck (2004, pp. 424) writes of "the rough shattering of AI in subfields—vision, natural language, decision theory, genetic algorithms, robotics ... and these with own sub-subfield—that would hardly have anything to say to each other."
  13. Jump up to:a b c This list of intelligent traits is based on the topics covered by the major AI textbooks, including:
  14. Jump up to:a b c Biological intelligence vs. intelligence in general:
    • Russell & Norvig 2003, pp. 2–3, who make the analogy with aeronautical engineering.
    • McCorduck 2004, pp. 100–101, who writes that there are "two major branches of artificial intelligence: one aimed at producing intelligent behavior regardless of how it was accomplished, and the other aimed at modeling intelligent processes found in nature, particularly human ones."
    • Kolata 1982, a paper in Science, which describes McCarthy'sindifference to biological models. Kolata quotes McCarthy as writing: "This is AI, so we don't care if it's psychologically real""Archived copy"Archived from the original on 7 July 2016. Retrieved 16 February 2016.. McCarthy recently reiterated his position at the AI@50 conference where he said "Artificial intelligence is not, by definition, simulation of human intelligence" (Maker 2006).
  15. Jump up to:a b c Neats vs. scruffies:
  16. Jump up to:a b c Symbolic vs. sub-symbolic AI:
  17. Jump up to:a b General intelligence (strong AI) is discussed in popular introductions to AI:
  18. Jump up^ See the Dartmouth proposal, under Philosophy, below.
  19. Jump up^ This is a central idea of Pamela McCorduck's Machines Who Think. She writes: "I like to think of artificial intelligence as the scientific apotheosis of a venerable cultural tradition." (McCorduck 2004, p. 34) "Artificial intelligence in one form or another is an idea that has pervaded Western intellectual history, a dream in urgent need of being realized." (McCorduck 2004, p. xviii) "Our history is full of attempts—nutty, eerie, comical, earnest, legendary and real—to make artificial intelligences, to reproduce what is the essential us—bypassing the ordinary means. Back and forth between myth and reality, our imaginations supplying what our workshops couldn't, we have engaged for a long time in this odd form of self-reproduction." (McCorduck 2004, p. 3) She traces the desire back to its Hellenistic roots and calls it the urge to "forge the Gods." (McCorduck 2004, pp. 340–400)
  20. Jump up^ "Stephen Hawking believes AI could be mankind's last accomplishment"BetaNews. 21 October 2016. Archivedfrom the original on 28 August 2017.
  21. Jump up to:a b Ford, Martin; Colvin, Geoff (6 September 2015). "Will robots create more jobs than they destroy?"The Guardian. Retrieved 13 January 2018.
  22. Jump up to:a b AI applications widely used behind the scenes:
  23. Jump up to:a b AI in myth:
  24. Jump up to:a b Russell & Norvig 2009, p. 16.
  25. Jump up^ AI in early science fiction.
  26. Jump up^ Formal reasoning:
  27. Jump up to:a b AI's immediate precursors:
  28. Jump up^ Dartmouth conference:
  29. Jump up^ Hegemony of the Dartmouth conference attendees:
  30. Jump up^ Russell & Norvig 2003, p. 18.
  31. Jump up^ Schaeffer J. (2009) Didn’t Samuel Solve That Game?. In: One Jump Ahead. Springer, Boston, MA
  32. Jump up^ Samuel, A. L. (July 1959). "Some Studies in Machine Learning Using the Game of Checkers". IBM Journal of Research and Development3 (3): 210–229. doi:10.1147/rd.33.0210.
  33. Jump up^ "Golden years" of AI (successful symbolic reasoning programs 1956–1973):The programs described are Arthur Samuel's checkers program for the IBM 701Daniel Bobrow's STUDENTNewell and Simon's Logic Theorist and Terry Winograd's SHRDLU.
  34. Jump up^ DARPA pours money into undirected pure research into AI during the 1960s:
  35. Jump up^ AI in England:
  36. Jump up^ Lighthill 1973.
  37. Jump up to:a b Expert systems:
  38. Jump up to:a b Formal methods are now preferred ("Victory of the neats"):
  39. Jump up^ McCorduck 2004, pp. 480–483.
  40. Jump up^ Markoff 2011.
  41. Jump up^ Administrator. "Kinect's AI breakthrough explained"i-programmer.infoArchived from the original on 1 February 2016.
  42. Jump up^ Rowinski, Dan (15 January 2013). "Virtual Personal Assistants & The Future Of Your Smartphone [Infographic]"ReadWriteArchived from the original on 22 December 2015.
  43. Jump up^ "Artificial intelligence: Google's AlphaGo beats Go master Lee Se-dol"BBC News. 12 March 2016. Archived from the original on 26 August 2016. Retrieved 1 October 2016.
  44. Jump up^ "After Win in China, AlphaGo's Designers Explore New AI". 27 May 2017. Archived from the original on 2 June 2017.
  45. Jump up^ "World's Go Player Ratings". May 2017. Archived from the original on 1 April 2017.
  46. Jump up^ "柯洁迎19岁生日 雄踞人类世界排名第一已两年" (in Chinese). May 2017. Archived from the original on 11 August 2017.
  47. Jump up to:a b Clark, Jack (8 December 2015). "Why 2015 Was a Breakthrough Year in Artificial Intelligence"Bloomberg NewsArchived from the original on 23 November 2016. Retrieved 23 November 2016After a half-decade of quiet breakthroughs in artificial intelligence, 2015 has been a landmark year. Computers are smarter and learning faster than ever.
  48. Jump up^ Domingos 2015, Chapter 5.
  49. Jump up^ Domingos 2015, Chapter 7.
  50. Jump up^ Lindenbaum, M., Markovitch, S., & Rusakov, D. (2004). Selective sampling for nearest neighbor classifiers. Machine learning, 54(2), 125-152.
  51. Jump up^ Domingos 2015, Chapter 1.
  52. Jump up^ Intractability and efficiency and the combinatorial explosion:
  53. Jump up^ Domingos 2015, Chapter 2, Chapter 3.
  54. Jump up^ Hart, P. E.; Nilsson, N. J.; Raphael, B. (1972). "Correction to "A Formal Basis for the Heuristic Determination of Minimum Cost Paths"". SIGART Newsletter37: 28–29. doi:10.1145/1056777.1056779.
  55. Jump up^ Domingos 2015, Chapter 6, Chapter 7.
  56. Jump up^ Domingos 2015, p. 286.
  57. Jump up^ "Single pixel change fools AI programs"BBC News. 3 November 2017. Retrieved 12 March 2018.
  58. Jump up^ "AI Has a Hallucination Problem That's Proving Tough to Fix"WIRED. 2018. Retrieved 12 March 2018.
  59. Jump up^ Goodfellow, Ian J., Jonathon Shlens, and Christian Szegedy. "Explaining and harnessing adversarial examples." arXiv preprint arXiv:1412.6572 (2014).
  60. Jump up^ Problem solving, puzzle solving, game playing and deduction:
  61. Jump up^ Uncertain reasoning:
  62. Jump up^ Psychological evidence of sub-symbolic reasoning:
  63. Jump up^ Knowledge representation:
  64. Jump up^ Knowledge engineering:
  65. Jump up to:a b Representing categories and relations: Semantic networksdescription logicsinheritance (including frames and scripts):
  66. Jump up to:a b Representing events and time:Situation calculusevent calculusfluent calculus (including solving the frame problem):
  67. Jump up to:a b Causal calculus:
  68. Jump up to:a b Representing knowledge about knowledge: Belief calculusmodal logics:
  69. Jump up^ Sikos, Leslie F. (June 2017). Description Logics in Multimedia Reasoning. Cham: Springer. doi:10.1007/978-3-319-54066-5ISBN 978-3-319-54066-5Archived from the original on 29 August 2017.
  70. Jump up^ Ontology:
  71. Jump up^ Bertini, M; Del Bimbo, A; Torniai, C (2006). "Automatic annotation and semantic retrieval of video sequences using multimedia ontologies". MM ‘06 Proceedings of the 14th ACM international conference on Multimedia. 14th ACM international conference on Multimedia. Santa Barbara: ACM. pp. 679–682.
  72. Jump up^ Qualification problem:While McCarthy was primarily concerned with issues in the logical representation of actions, Russell & Norvig 2003 apply the term to the more general issue of default reasoning in the vast network of assumptions underlying all our commonsense knowledge
  1.  Default reasoning and default logicnon-monotonic logicscircumscriptionclosed world assumptionabduction (Poole et al.places abduction under "default reasoning". Luger et al. places this under "uncertain reasoning"):
  2. Jump up^ Breadth of commonsense knowledge:
  3. Jump up^ Dreyfus & Dreyfus 1986.
  4. Jump up^ Gladwell 2005.
  5. Jump up to:a b Expert knowledge as embodied intuition:
  6. Jump up^ Planning:
  7. Jump up to:a b Information value theory:
  8. Jump up^ Classical planning:
  9. Jump up^ Planning and acting in non-deterministic domains: conditional planning, execution monitoring, replanning and continuous planning:
  10. Jump up^ Multi-agent planning and emergent behavior:
  11. Jump up^ Alan Turing discussed the centrality of learning as early as 1950, in his classic paper "Computing Machinery and Intelligence".(Turing 1950) In 1956, at the original Dartmouth AI summer conference, Ray Solomonoff wrote a report on unsupervised probabilistic machine learning: "An Inductive Inference Machine".(Solomonoff 1956)
  12. Jump up^ This is a form of Tom Mitchell's widely quoted definition of machine learning: "A computer program is set to learn from an experience E with respect to some task T and some performance measure P if its performance on T as measured by P improves with experience E."
  13. Jump up^ Learning:
  14. Jump up^ Reinforcement learning:
  15. Jump up^ Weng et al. 2001.
  16. Jump up^ Lungarella et al. 2003.
  17. Jump up^ Asada et al. 2009.
  18. Jump up^ Oudeyer 2010.
  19. Jump up^ Natural language processing:
  20. Jump up^ "Versatile question answering systems: seeing in synthesis"Archived 1 February 2016 at the Wayback Machine., Mittal et al., IJIIDS, 5(2), 119–142, 2011
  21. Jump up^ Applications of natural language processing, including information retrieval (i.e. text mining) and machine translation:
  22. Jump up^ Machine perception:
  23. Jump up^ Computer vision:
  24. Jump up^ Speech recognition:
  25. Jump up^ Object recognition:
  26. Jump up^ Robotics:
  27. Jump up to:a b Moving and configuration space:
  28. Jump up to:a b Tecuci 2012.
  29. Jump up^ Robotic mapping (localization, etc):
  30. Jump up^ Kismet.
  31. Jump up^ Thro 1993.
  32. Jump up^ Edelson 1991.
  33. Jump up^ Tao & Tan 2005.
  34. Jump up^ James 1884.
  35. Jump up^ Picard 1995.
  36. Jump up^ Kleine-Cosack 2006: "The introduction of emotion to computer science was done by Pickard (sic) who created the field of affective computing."
  37. Jump up^ Diamond 2003: "Rosalind Picard, a genial MIT professor, is the field's godmother; her 1997 book, Affective Computing, triggered an explosion of interest in the emotional side of computers and their users."
  38. Jump up^ Emotion and affective computing:
  39. Jump up to:a b c Roberts, Jacob (2016). "Thinking Machines: The Search for Artificial Intelligence"Distillations2 (2): 14–23. Retrieved 20 March 2018.
  40. Jump up^ Gerald EdelmanIgor Aleksander and others have argued that artificial consciousness is required for strong AI. (Aleksander 1995Edelman 2007)
  41. Jump up to:a b Artificial brain arguments: AI requires a simulation of the operation of the human brainA few of the people who make some form of the argument:The most extreme form of this argument (the brain replacement scenario) was put forward by Clark Glymour in the mid-1970s and was touched on by Zenon Pylyshyn and John Searle in 1980.
  42. Jump up^ Nils Nilsson writes: "Simply put, there is wide disagreement in the field about what AI is all about" (Nilsson 1983, p. 10).
  43. Jump up^ Haugeland 1985, p. 255.
  44. Jump up^ Law 1994.
  45. Jump up^ Bach 2008.
  46. Jump up to:a b c Shapiro, Stuart C. (1992), "Artificial Intelligence", in Stuart C. Shapiro (ed.), Encyclopedia of Artificial Intelligence, 2nd edition (New York: John Wiley & Sons): 54–57. 4 December 2016.
  47. Jump up^ Haugeland 1985, pp. 112–117
  48. Jump up^ The most dramatic case of sub-symbolic AI being pushed into the background was the devastating critique of perceptrons by Marvin Minsky and Seymour Papert in 1969. See History of AIAI winter, or Frank Rosenblatt.
  49. Jump up^ Cognitive simulation, Newell and Simon, AI at CMU (then called Carnegie Tech):
  50. Jump up^ Soar (history):
  51. Jump up^ McCarthy and AI research at SAIL and SRI International:
  52. Jump up^ AI research at Edinburgh and in France, birth of Prolog:
  53. Jump up^ AI at MIT under Marvin Minsky in the 1960s :
  54. Jump up^ Cyc:
  55. Jump up^ Knowledge revolution:
  56. Jump up^ Embodied approaches to AI:
  57. Jump up^ Revival of connectionism:
  58. Jump up^ Computational intelligence
  59. Jump up^ Hutter 2012.
  60. Jump up^ Langley 2011.
  61. Jump up^ Katz 2012.
  62. Jump up^ Norvig 2012.
  63. Jump up^ The intelligent agent paradigm:The definition used in this article, in terms of goals, actions, perception and environment, is due to Russell & Norvig (2003). Other definitions also include knowledge and learning as additional criteria.
  64. Jump up^ Agent architectureshybrid intelligent systems:
  65. Jump up^ Hierarchical control system:
  66. Jump up^ Search algorithms:
  67. Jump up^ Forward chainingbackward chainingHorn clauses, and logical deduction as search:
  68. Jump up^ State space search and planning:
  69. Jump up^ Uninformed searches (breadth first searchdepth first searchand general state space search):
  70. Jump up^ Heuristic or informed searches (e.g., greedy best first and A*):
  71. Jump up^ Optimization searches:
  72. Jump up^ Artificial life and society based learning:
  73. Jump up^ Genetic programming and genetic algorithms:
  74. Jump up^ Logic:
  75. Jump up^ Satplan:
  76. Jump up^ Explanation based learningrelevance based learninginductive logic programmingcase based reasoning:
  77. Jump up^ Propositional logic:
  78. Jump up^ First-order logic and features such as equality:
  79. Jump up^ Fuzzy logic:
  80. Jump up^ "The Belief Calculus and Uncertain Reasoning", Yen-Teh Hsia
  81. Jump up
  1.  Stochastic methods for uncertain reasoning:
  2. Jump up^ Bayesian networks:
  3. Jump up^ Bayesian inference algorithm:
  4. Jump up^ Domingos 2015, p. 210.
  5. Jump up^ Bayesian learning and the expectation-maximization algorithm:
  6. Jump up^ Bayesian decision theory and Bayesian decision networks:
  7. Jump up to:a b c Stochastic temporal models:Dynamic Bayesian networks:Hidden Markov model:Kalman filters:
  8. Jump up^ Domingos 2015, p. 160.
  9. Jump up^ decision theory and decision analysis:
  10. Jump up^ Markov decision processes and dynamic decision networks:
  11. Jump up^ Game theory and mechanism design:
  12. Jump up^ Statistical learning methods and classifiers:
  13. Jump up^ Decision tree:
  14. Jump up^ Domingos 2015, p. 88.
  15. Jump up to:a b Neural networks and connectionism:
  16. Jump up^ Domingos 2015, p. 187.
  17. Jump up^ K-nearest neighbor algorithm:
  18. Jump up^ Domingos 2015, p. 188.
  19. Jump up^ kernel methods such as the support vector machine:
  20. Jump up^ Gaussian mixture model:
  21. Jump up^ Domingos 2015, p. 152.
  22. Jump up^ Naive Bayes classifier:
  23. Jump up^ Classifier performance:
  24. Jump up^ Domingos 2015, Chapter 4.
  25. Jump up^ "Why Deep Learning Is Suddenly Changing Your Life"Fortune. 2016. Retrieved 12 March 2018.
  26. Jump up^ "Google leads in the race to dominate artificial intelligence"The Economist. 2017. Retrieved 12 March 2018.
  27. Jump up^ Feedforward neural networksperceptrons and radial basis networks:
  28. Jump up^ Competitive learningHebbian coincidence learning, Hopfield networks and attractor networks:
  29. Jump up^ Seppo Linnainmaa (1970). The representation of the cumulative rounding error of an algorithm as a Taylor expansion of the local rounding errors. Master's Thesis (in Finnish), Univ. Helsinki, 6–7.
  30. Jump up^ Griewank, Andreas (2012). Who Invented the Reverse Mode of Differentiation?. Optimization Stories, Documenta Matematica, Extra Volume ISMP (2012), 389–400.
  31. Jump up^ Paul Werbos, "Beyond Regression: New Tools for Prediction and Analysis in the Behavioral Sciences", PhD thesis, Harvard University, 1974.
  32. Jump up^ Paul Werbos (1982). Applications of advances in nonlinear sensitivity analysis. In System modeling and optimization (pp. 762–770). Springer Berlin Heidelberg. Online Archived 14 April 2016 at the Wayback Machine.
  33. Jump up^ Backpropagation:
  34. Jump up^ Hierarchical temporal memory:
  35. Jump up^ "Artificial intelligence can 'evolve' to solve problems"Science | AAAS. 10 January 2018. Retrieved 7 February 2018.
  36. Jump up to:a b c d Schmidhuber, J. (2015). "Deep Learning in Neural Networks: An Overview". Neural Networks61: 85–117. arXiv:1404.7828Freely accessibledoi:10.1016/j.neunet.2014.09.003.
  37. Jump up to:a b Ian Goodfellow, Yoshua Bengio, and Aaron Courville (2016). Deep Learning. MIT Press. Online Archived 16 April 2016 at the Wayback Machine.
  38. Jump up^ Hinton, G.; Deng, L.; Yu, D.; Dahl, G.; Mohamed, A.; Jaitly, N.; Senior, A.; Vanhoucke, V.; Nguyen, P.; Sainath, T.; Kingsbury, B. (2012). "Deep Neural Networks for Acoustic Modeling in Speech Recognition --- The shared views of four research groups". IEEE Signal Processing Magazine29 (6): 82–97. doi:10.1109/msp.2012.2205597.
  39. Jump up^ Schmidhuber, Jürgen (2015). "Deep Learning"Scholarpedia10 (11): 32832. doi:10.4249/scholarpedia.32832Archivedfrom the original on 19 April 2016.
  40. Jump up^ Rina Dechter (1986). Learning while searching in constraint-satisfaction problems. University of California, Computer Science Department, Cognitive Systems Laboratory.Online Archived19 April 2016 at the Wayback Machine.
  41. Jump up^ Igor Aizenberg, Naum N. Aizenberg, Joos P.L. Vandewalle (2000). Multi-Valued and Universal Binary Neurons: Theory, Learning and Applications. Springer Science & Business Media.
  42. Jump up^ Ivakhnenko, Alexey (1965). Cybernetic Predicting Devices. Kiev: Naukova Dumka.
  43. Jump up^ Ivakhnenko, Alexey (1971). "Polynomial theory of complex systems". IEEE Transactions on Systems, Man and Cybernetics (4): 364–378.
  44. Jump up^ Hinton 2007.
  45. Jump up^ Research, AI (23 October 2015). "Deep Neural Networks for Acoustic Modeling in Speech Recognition" Retrieved 23 October 2015.
  46. Jump up^ Fukushima, K. (1980). "Neocognitron: A self-organizing neural network model for a mechanism of pattern recognition unaffected by shift in position". Biological Cybernetics36: 193–202. doi:10.1007/bf00344251PMID 7370364.
  47. Jump up^ Yann LeCun (2016). Slides on Deep Learning OnlineArchived 23 April 2016 at the Wayback Machine.
  48. Jump up^ Silver, David; Schrittwieser, Julian; Simonyan, Karen; Antonoglou, Ioannis; Huang, Aja; Guez, Arthur; Hubert, Thomas; Baker, Lucas; Lai, Matthew; Bolton, Adrian; Chen, Yutian; Lillicrap, Timothy; Fan, Hui; Sifre, Laurent; Driessche, George van den; Graepel, Thore; Hassabis, Demis (19 October 2017). "Mastering the game of Go without human knowledge"Nature550 (7676): 354–359. doi:10.1038/nature24270ISSN 0028-0836AlphaGo Lee... 12 convolutional layersclosed access publication – behind paywall
  49. Jump up^ Recurrent neural networksHopfield nets:
  50. Jump up^ Hyötyniemi, Heikki (1996). "Turing machines are recurrent neural networks". Proceedings of STeP '96/Publications of the Finnish Artificial Intelligence Society: 13–24.
  51. Jump up^ P. J. Werbos. Generalization of backpropagation with application to a recurrent gas market model" Neural Networks 1, 1988.
  52. Jump up^ A. J. Robinson and F. Fallside. The utility driven dynamic error propagation network. Technical Report CUED/F-INFENG/TR.1, Cambridge University Engineering Department, 1987.
  53. Jump up^ R. J. Williams and D. Zipser. Gradient-based learning algorithms for recurrent networks and their computational complexity. In Back-propagation: Theory, Architectures and Applications. Hillsdale, NJ: Erlbaum, 1994.
  54. Jump up^ Sepp Hochreiter (1991), Untersuchungen zu dynamischen neuronalen Netzen Archived 6 March 2015 at the Wayback Machine., Diploma thesis. Institut f. Informatik, Technische Univ. Munich. Advisor: J. Schmidhuber.
  55. Jump up^ Schmidhuber, J. (1992). "Learning complex, extended sequences using the principle of history compression". Neural Computation4: 234–242. CiteSeerX accessibledoi:10.1162/neco.1992.4.2.234.
  56. Jump up^ Hochreiter, Sepp; and Schmidhuber, JürgenLong Short-Term Memory, Neural Computation, 9(8):1735–1780, 1997
  57. Jump up^ Alex Graves, Santiago Fernandez, Faustino Gomez, and Jürgen Schmidhuber (2006). Connectionist temporal classification: Labelling unsegmented sequence data with recurrent neural nets. Proceedings of ICML’06, pp. 369–376.
  58. Jump up^ Hannun, Awni; Case, Carl; Casper, Jared; Catanzaro, Bryan; Diamos, Greg; Elsen, Erich; Prenger, Ryan; Satheesh, Sanjeev; Sengupta, Shubho; Coates, Adam; Ng, Andrew Y. (2014). "Deep Speech: Scaling up end-to-end speech recognition". arXiv:1412.5567Freely accessible.
  59. Jump up^ Hasim Sak and Andrew Senior and Francoise Beaufays (2014). Long Short-Term Memory recurrent neural network architectures for large scale acoustic modeling. Proceedings of Interspeech 2014.
  60. Jump up^ Li, Xiangang; Wu, Xihong (2015). "Constructing Long Short-Term Memory based Deep Recurrent Neural Networks for Large Vocabulary Speech Recognition". arXiv:1410.4281Freely accessible.
  61. Jump up^ Haşim Sak, Andrew Senior, Kanishka Rao, Françoise Beaufays and Johan Schalkwyk (September 2015): Google voice search: faster and more accurate. Archived 9 March 2016 at the Wayback Machine.
  62. Jump up^ Sutskever, Ilya; Vinyals, Oriol; Le, Quoc V. (2014). "Sequence to Sequence Learning with Neural Networks". arXiv:1409.3215Freely accessible.
  63. Jump up^ Jozefowicz, Rafal; Vinyals, Oriol; Schuster, Mike; Shazeer, Noam; Wu, Yonghui (2016). "Exploring the Limits of Language Modeling". arXiv:1602.02410Freely accessible.
  64. Jump up^ Gillick, Dan; Brunk, Cliff; Vinyals, Oriol; Subramanya, Amarnag (2015). "Multilingual Language Processing From Bytes". arXiv:1512.00103Freely accessible.
  65. Jump up^ Vinyals, Oriol; Toshev, Alexander; Bengio, Samy; Erhan, Dumitru (2015). "Show and Tell: A Neural Image Caption Generator". arXiv:1411.4555Freely accessible.
  66. Jump up^ Lisp:
  67. Jump up^ Prolog:
  68. Jump up^ "C++ Java". Retrieved 6 December 2017.
  69. Jump up^ Ferris, Robert (7 April 2016). "How Steve Jobs' friend changed the world of math"CNBC. Retrieved 28 February 2018.
  70. Jump up to:a b The Turing test:
    Turing's original publication:
    Historical influence and philosophical implications:
  71. Jump up^ Mathematical definitions of intelligence:
  72. Jump up^ O'Brien & Marakas 2011.
  73. Jump up to:a b Russell & Norvig 2009, p. 1.
  74. Jump up^ CNN 2006.
  75. Jump up^ N. Aletras; D. Tsarapatsanis; D. Preotiuc-Pietro; V. Lampos (2016). "Predicting judicial decisions of the European Court of Human Rights: a Natural Language Processing perspective"PeerJ Computer ScienceArchived from the original on 29 October 2016.
  76. Jump up^ "The Economist Explains: Why firms are piling into artificial intelligence"The Economist. 31 March 2016. Archived from the original on 8 May 2016. Retrieved 19 May 2016.
  77. Jump up^ Lohr, Steve (28 February 2016). "The Promise of Artificial Intelligence Unfolds in Small Steps"The New York TimesArchived from the original on 29 February 2016. Retrieved 29 February 2016.
  78. Jump up^ Wakefield, Jane (15 June 2016). "Social media 'outstrips TV' as news source for young people"BBC NewsArchived from the original on 24 June 2016.
  79. Jump up^ Smith, Mark (22 July 2016). "So you think you chose to read this article?"BBC NewsArchived from the original on 25 July 2016.
  80. Jump up^ Dina Bass (20 September 2016). "Microsoft Develops AI to Help Cancer Doctors Find the Right Treatments". Bloomberg. Archived from the original on 11 May 2017.
  81. Jump up^ Gallagher, James (26 January 2017). "Artificial intelligence 'as good as cancer doctors'"BBC NewsArchived from the original on 26 January 2017. Retrieved 26 January 2017.
  82. Jump up^ [1], Langen, Pauline A.; Jeffrey S. Katz & Gayle Dempsey, "Remote monitoring of high-risk patients using artificial intelligence"
  83. Jump up^ Senthilingam, Meera (12 May 2016). "Are Autonomous Robots Your next Surgeons?"CNN. Cable News Network. Archivedfrom the original on 3 December 2016. Retrieved 4 December2016.
  84. Jump up^ Markoff, John (16 February 2011). "On 'Jeopardy!' Watson Win Is All but Trivial"The New York TimesArchived from the original on 22 September 2017.
  85. Jump up^ Ng, Alfred (7 August 2016). "IBM's Watson gives proper diagnosis after doctors were stumped"NY Daily NewsArchived from the original on 22 September 2017.
  86. Jump up^ "33 Corporations Working On Autonomous Vehicles". CB Insights. N.p., 11 August 2016. 12 November 2016.
  87. Jump up^ West, Darrell M. "Moving forward: Self-driving vehicles in China, Europe, Japan, Korea, and the United States". Center for Technology Innovation at Brookings. N.p., September 2016. 12 November 2016.
  88. Jump up^ Burgess, Matt. "The UK is about to Start Testing Self-Driving Truck Platoons"WIREDArchived from the original on 22 September 2017. Retrieved 20 September 2017.
  89. Jump up^ Davies, Alex. "World's First Self-Driving Semi-Truck Hits the 
  1.  Davies, Alex. "World's First Self-Driving Semi-Truck Hits the Road"WIREDArchived from the original on 28 October 2017. Retrieved 20 September 2017.
  2. Jump up^ McFarland, Matt. "Google's artificial intelligence breakthrough may have a huge impact on self-driving cars and much more". The Washington Post 25 February 2015. Infotrac Newsstand. 24 October 2016
  3. Jump up^ "Programming safety into self-driving cars". National Science Foundation. N.p., 2 February 2015. 24 October 2016.
  4. Jump up^ ArXiv, E. T. (26 October 2015). Why Self-Driving Cars Must Be Programmed to Kill. Retrieved 17 November 2017, from
  5. Jump up^ O'Neill,, Eleanor (31 July 2016). "Accounting, automation and AI"www.icas.comArchived from the original on 18 November 2016. Retrieved 18 November 2016.
  6. Jump up^ Robots Beat Humans in Trading Battle. Archived 9 September 2009 at the Wayback Machine. (8 August 2001)
  7. Jump up^ "CTO Corner: Artificial Intelligence Use in Financial Services – Financial Services Roundtable"Financial Services Roundtable. 2 April 2015. Archived from the original on 18 November 2016. Retrieved 18 November 2016.
  8. Jump up^ Marwala, Tshilidzi; Hurwitz, Evan (2017). Artificial Intelligence and Economic Theory: Skynet in the Market. London: SpringerISBN 978-3-319-66104-9.
  9. Jump up^ "Why AI researchers like video games"The EconomistArchived from the original on 5 October 2017.
  10. Jump up^ Yannakakis, G. N. (2012, May). Game AI revisited. In Proceedings of the 9th conference on Computing Frontiers (pp. 285–292). ACM.
  11. Jump up^ Brooks 1991.
  12. Jump up^ "Hacking Roomba"hackingroomba.comArchived from the original on 18 October 2009.
  13. Jump up^ "A self-organizing thousand-robot swarm" 14 August 2014. Archived from the original on 4 May 2017.
  14. Jump up to:a b c d "Watch An Autonomous Robot Swarm Form 2D Starfishes"Creators.
  15. Jump up^ Rainie, Lee; Janna; erson (8 February 2017). "Theme 2: Good things lie ahead"Archived from the original on 3 July 2017.
  16. Jump up^ Lynley, Matthew. "SoundHound raises $75M to bring its voice-enabled AI everywhere"Archived from the original on 13 September 2017.
  17. Jump up^ Manyika, James; Chui, Michael; Bughin, Jaques; Brown, Brad; Dobbs, Richard; Roxburgh, Charles; Byers, Angela Hung (May 2011). "Big Data: The next frontier for innovation, competition, and productivity". McKinsey Global Institute. Archived from the original on 6 March 2013. Retrieved 16 January 2016.
  18. Jump up^ "NY gets new boot camp for data scientists: It's free but harder to get into than Harvard"Venture BeatArchived from the original on 15 February 2016. Retrieved 21 February 2016.
  19. Jump up to:a b "Partnership on Artificial Intelligence to Benefit People and Society". N.p., n.d. 24 October 2016.
  20. Jump up^ Fiegerman, Seth. "Facebook, Google, Amazon Create Group to Ease AI Concerns". CNNMoney. n.d. 4 December 2016.
  21. Jump up^ Dartmouth proposal:
  22. Jump up^ The physical symbol systems hypothesis:
  23. Jump up^ Dreyfus criticized the necessary condition of the physical symbol system hypothesis, which he called the "psychological assumption": "The mind can be viewed as a device operating on bits of information according to formal rules." (Dreyfus 1992, p. 156)
  24. Jump up^ Dreyfus' critique of artificial intelligence:
  25. Jump up^ Gödel 1951: in this lecture, Kurt Gödel uses the incompleteness theorem to arrive at the following disjunction: (a) the human mind is not a consistent finite machine, or (b) there exist Diophantine equations for which it cannot decide whether solutions exist. Gödel finds (b) implausible, and thus seems to have believed the human mind was not equivalent to a finite machine, i.e., its power exceeded that of any finite machine. He recognized that this was only a conjecture, since one could never disprove (b). Yet he considered the disjunctive conclusion to be a "certain fact".
  26. Jump up^ The Mathematical Objection:Making the Mathematical Objection:Refuting Mathematical Objection:Background:
    • Gödel 1931, Church 1936, Kleene 1935, Turing 1937
  27. Jump up^ Graham Oppy (20 January 2015). "Gödel's Incompleteness Theorems"Stanford Encyclopedia of Philosophy. Retrieved 27 April 2016These Gödelian anti-mechanist arguments are, however, problematic, and there is wide consensus that they fail.
  28. Jump up^ Stuart J. RussellPeter Norvig (2010). "26.1.2: Philosophical Foundations/Weak AI: Can Machines Act Intelligently?/The mathematical objection". Artificial Intelligence: A Modern Approach (3rd ed.). Upper Saddle River, NJ: Prentice HallISBN 0-13-604259-7...even if we grant that computers have limitations on what they can prove, there is no evidence that humans are immune from those limitations.
  29. Jump up^ Mark Colyvan. An introduction to the philosophy of mathematics. Cambridge University Press, 2012. From 2.2.2, 'Philosophical significance of Gödel's incompleteness results': "The accepted wisdom (with which I concur) is that the Lucas-Penrose arguments fail."
  30. Jump up^ Russel, Stuart., Daniel Dewey, and Max Tegmark. Research Priorities for Robust and Beneficial Artificial Intelligence. AI Magazine 36:4 (2015). 8 December 2016.
  31. Jump up^ "Stephen Hawking warns artificial intelligence could end mankind"BBC NewsArchived from the original on 30 October 2015. Retrieved 30 October 2015.
  32. Jump up^ Holley, Peter (28 January 2015). "Bill Gates on dangers of artificial intelligence: 'I don't understand why some people are not concerned'"The Washington PostISSN 0190-8286Archived from the original on 30 October 2015. Retrieved 30 October 2015.
  33. Jump up^ Gibbs, Samuel. "Elon Musk: artificial intelligence is our biggest existential threat"the GuardianArchived from the original on 30 October 2015. Retrieved 30 October 2015.
  34. Jump up^ Post, Washington. "Tech titans like Elon Musk are spending $1 billion to save you from terminators"Archived from the original on 7 June 2016.
  35. Jump up^ Müller, Vincent C.; Bostrom, Nick (2014). "Future Progress in Artificial Intelligence: A Poll Among Experts" (PDF)AI Matters1 (1): 9–11. doi:10.1145/2639475.2639478Archived (PDF)from the original on 15 January 2016.
  36. Jump up^ "Is artificial intelligence really an existential threat to humanity?"Bulletin of the Atomic ScientistsArchived from the original on 30 October 2015. Retrieved 30 October 2015.
  37. Jump up^ "The case against killer robots, from a guy actually working on artificial intelligence"Fusion.netArchived from the original on 4 February 2016. Retrieved 31 January 2016.
  38. Jump up^ "Will artificial intelligence destroy humanity? Here are 5 reasons not to worry"VoxArchived from the original on 30 October 2015. Retrieved 30 October 2015.
  39. Jump up^ "The mysterious artificial intelligence company Elon Musk invested in is developing game-changing smart computers"Tech InsiderArchived from the original on 30 October 2015. Retrieved 30 October 2015.
  40. Jump up^ Clark, Jack. "Musk-Backed Group Probes Risks Behind Artificial Intelligence"Bloomberg.comArchived from the original on 30 October 2015. Retrieved 30 October 2015.
  41. Jump up^ "Elon Musk Is Donating $10M Of His Own Money To Artificial Intelligence Research"Fast CompanyArchived from the original on 30 October 2015. Retrieved 30 October 2015.
  42. Jump up^ "Stephen Hawking, Elon Musk, and Bill Gates Warn About Artificial Intelligence"ObserverArchived from the original on 30 October 2015. Retrieved 30 October 2015.
  43. Jump up^ In the early 1970s, Kenneth Colby presented a version of Weizenbaum's ELIZA known as DOCTOR which he promoted as a serious therapeutic tool. (Crevier 1993, pp. 132–144)
  44. Jump up^ Joseph Weizenbaum's critique of AI:Weizenbaum (the AI researcher who developed the first chatterbot program, ELIZA) argued in 1976 that the misuse of artificial intelligence has the potential to devalue human life.
  45. Jump up^ E McGaughey, 'Will Robots Automate Your Job Away? Full Employment, Basic Income, and Economic Democracy' (2018) SSRN, part 2(3)
  46. Jump up^ "Automation and anxiety"The Economist. 9 May 2015. Retrieved 13 January 2018.
  47. Jump up^ Lohr, Steve (2017). "Robots Will Take Jobs, but Not as Fast as Some Fear, New Report Says"The New York Times. Retrieved 13 January 2018.
  48. Jump up^ "The future of employment: How susceptible are jobs to computerisation?"Technological Forecasting and Social Change114: 254–280. 1 January 2017. doi:10.1016/j.techfore.2016.08.019ISSN 0040-1625.
  49. Jump up^ Arntz, Melanie, Terry Gregory, and Ulrich Zierahn. "The risk of automation for jobs in OECD countries: A comparative analysis." OECD Social, Employment, and Migration Working Papers 189 (2016). p. 33.
  50. Jump up^ Mahdawi, Arwa (26 June 2017). "What jobs will still be around in 20 years? Read this to prepare your future"The Guardian. Retrieved 13 January 2018.
  51. Jump up^ Wendell Wallach (2010). Moral Machines, Oxford University Press.
  52. Jump up^ Wallach, pp 37–54.
  53. Jump up^ Wallach, pp 55–73.
  54. Jump up^ Wallach, Introduction chapter.
  55. Jump up to:a b Michael Anderson and Susan Leigh Anderson (2011), Machine Ethics, Cambridge University Press.
  56. Jump up to:a b "Machine Ethics" Archived from the original on 29 November 2014.
  57. Jump up^ Rubin, Charles (Spring 2003). "Artificial Intelligence and Human Nature |`The New Atlantis"1: 88–100. Archived from the original on 11 June 2012.
  58. Jump up^ Rawlinson, Kevin. "Microsoft's Bill Gates insists AI is a threat". BBC News. Archived from the original on 29 January 2015. Retrieved 30 January 2015.
  59. Jump up^ Brooks, Rodney (10 November 2014). "artificial intelligence is a tool, not a threat". Archived from the original on 12 November 2014.
  60. Jump up^ Horst, Steven, (2005) "The Computational Theory of Mind" in The Stanford Encyclopedia of Philosophy
  61. Jump up^ This version is from Searle (1999), and is also quoted in Dennett 1991, p. 435. Searle's original formulation was "The appropriately programmed computer really is a mind, in the sense that computers given the right programs can be literally said to understand and have other cognitive states." (Searle 1980, p. 1). Strong AI is defined similarly by Russell & Norvig (2003, p. 947): "The assertion that machines could possibly act intelligently (or, perhaps better, act as if they were intelligent) is called the 'weak AI' hypothesis by philosophers, and the assertion that machines that do so are actually thinking (as opposed to simulating thinking) is called the 'strong AI' hypothesis."
  62. Jump up^ Searle's Chinese room argument:Discussion:
  63. Jump up^ Robot rights:Prematurity of:In fiction:
  64. Jump up^ Evans, Woody (2015). "Posthuman Rights: Dimensions of Transhuman Worlds"Teknokultura. Universidad Complutense, Madrid. Archived from the original on 28 December 2016. Retrieved 5 December 2016.
  65. Jump up^ maschafilm. "Content: Plug & Pray Film – Artificial Intelligence – Robots -"plugandpray-film.deArchived from the original on 12 February 2016.
  66. Jump up^ Omohundro, Steve (2008). The Nature of Self-Improving Artificial Intelligence. presented and distributed at the 2007 Singularity Summit, San Francisco, CA.
  67. Jump up to:a b c Technological singularity:
  68. Jump up^ Lemmons, Phil (April 1985). "Artificial Intelligence"BYTE. p. 125. Archived from the original on 20 April 2015. Retrieved 14 February 2015.
  69. Jump up^ Transhumanism:
  70. Jump up^ AI as evolution:
  71. Jump up to:a b c "When an AI finally kills someone, who will be responsible?". March 12, 2018.
  72. Jump up^ Anderson, Susan Leigh. "Asimov's "three laws of robotics" and machine metaethics." AI & Society 22.4 (2008): 477–493.
  73. Jump up^ McCauley, Lee (2007). "AI armageddon and the three laws of robotics". Ethics and Information Technology9 (2): 153–164. CiteSeerX accessibledoi:10.1007/s10676-007-9138-2.
  74. Jump up^ Galvan, Jill (1 January 1997). "Entering the Posthuman Collective in Philip K. Dick's "Do Androids Dream of Electric Sheep?"". Science Fiction Studies24 (3): 413–429. JSTOR 4240644.
  75. Jump up^ Buttazzo, G. (July 2001). "Artificial consciousness: Utopia or real possibility?"Computer (IEEE)34 (7): 24–30. doi:10.1109/2.933500Archived from the original on 30 December 2016. Retrieved 29 December 2016.
Subpages (1): AI textbooks