Editing Cognitive science (section)

==History==
The cognitive sciences began as an intellectual movement in the 1950s, called the [[cognitive revolution]]. Cognitive science has a prehistory traceable back to ancient Greek philosophical texts (see [[Plato]]'s ''[[Meno]]'' and [[Aristotle]]'s {{lang|la|[[De Anima]]}}); Modern philosophers such as [[Descartes]], [[David Hume]], [[Immanuel Kant]], [[Benedict de Spinoza]], [[Nicolas Malebranche]], [[Pierre Cabanis]], [[Leibniz]] and [[John Locke]], rejected [[scholasticism]] while mostly having never read Aristotle, and they were working with an entirely different set of tools and core concepts than those of the cognitive scientist.{{cn|date=September 2024}}

The modern culture of cognitive science can be traced back to the early [[cybernetics|cyberneticists]] in the 1930s and 1940s, such as [[Warren McCulloch]] and [[Walter Pitts]], who sought to understand the organizing principles of the mind. McCulloch and Pitts developed the first variants of what are now known as [[artificial neural networks]], models of computation inspired by the structure of [[biological neural networks]].<ref>{{Cite journal |last1=McCulloch |first1=W.S. |last2=Pitts |first2=W. |date=1943 |title=A logical calculus of the ideas immanent in nervous activity. |journal=Bulletin of Mathematical Biophysics |volume=5 |issue=4 |pages=115–133 |doi=10.1007/BF02478259}}</ref>

Another precursor was the early development of the [[theory of computation]] and the [[digital computer]] in the 1940s and 1950s. [[Kurt Gödel]], [[Alonzo Church]], [[Alan Turing]], and [[John von Neumann]] were instrumental in these developments. The modern computer, or [[Von Neumann architecture|Von Neumann machine]], would play a central role in cognitive science, both as a metaphor for the mind, and as a tool for investigation.<ref>{{Cite journal |last1=Alexandre |first1=Boris |last2=Navarro |first2=Jordan |last3=Reynaud |first3=Emanuelle |last4=Osiurak |first4=François |date=2019-05-01 |title=Which cognitive tools do we prefer to use, and is that preference rational? |url=https://www.sciencedirect.com/science/article/abs/pii/S0010027719300319 |journal=Cognition |volume=186 |pages=108–114 |doi=10.1016/j.cognition.2019.02.005 |pmid=30771701 |issn=0010-0277}}</ref>

The first instance of cognitive science experiments being done at an academic institution took place at [[MIT Sloan School of Management]], established by [[J.C.R. Licklider]] working within the psychology department and conducting experiments using computer memory as models for human cognition.<ref>{{cite book |last1=Hafner |first1=K. |last2=Lyon |first2=M. |year=1996 |title=Where wizards stay up late: The origins of the Internet |location=New York |publisher=Simon & Schuster |page=32 |isbn=0-684-81201-0 }}</ref>{{Unreliable source?|date=January 2025}} In 1959, [[Noam Chomsky]] published a scathing review of [[B. F. Skinner]]'s book ''[[Verbal Behavior]]''.<ref name="Chomsky 1959 26–58">{{Cite journal|last=Chomsky|first=Noam|date=1959|title=Review of Verbal behavior|journal=Language|volume=35|issue=1|pages=26–58|doi=10.2307/411334|jstor=411334|issn=0097-8507}}</ref> At the time, Skinner's [[behaviorist]] paradigm dominated the field of psychology within the United States. Most psychologists focused on functional relations between stimulus and response, without positing internal representations. Chomsky argued that in order to explain language, we needed a theory like [[generative grammar]], which not only attributed internal representations but characterized their underlying order.{{cn|date=September 2024}}

The term ''cognitive science'' was coined by [[Christopher Longuet-Higgins]] in his 1973 commentary on the [[Lighthill report]], which concerned the then-current state of [[artificial intelligence]] research.<ref>{{cite book |last=Longuet-Higgins |first=H. C. |year=1973 |chapter=Comments on the Lighthill Report and the Sutherland Reply |title=Artificial Intelligence: a paper symposium |publisher=Science Research Council |pages=35–37 |isbn=0-901660-18-3 }}</ref> In the same decade, the journal ''[[Cognitive Science (journal)|Cognitive Science]]'' and the [[Cognitive Science Society]] were founded.<ref>[http://www.cognitivesciencesociety.org/about_description.html Cognitive Science Society] {{webarchive|url=https://web.archive.org/web/20100717134015/http://www.cognitivesciencesociety.org/about_description.html |date=17 July 2010 }}</ref> The founding meeting of the [[Cognitive Science Society]] was held at the [[University of California, San Diego]] in 1979, which resulted in cognitive science becoming an internationally visible enterprise.<ref name="cogsci.ucsd.edu">{{cite web |url=http://www.cogsci.ucsd.edu/about-us/ucsd-cog-sci/ |title=UCSD Cognitive Science - UCSD Cognitive Science |access-date=8 July 2015 |archive-url=https://web.archive.org/web/20150709171712/http://www.cogsci.ucsd.edu/about-us/ucsd-cog-sci/ |archive-date=9 July 2015 |url-status=dead }}</ref> In 1972, [[Hampshire College]] started the first undergraduate education program in Cognitive Science, led by Neil Stillings. In 1982, with assistance from Professor Stillings, [[Vassar College]] became the first institution in the world to grant an undergraduate degree in Cognitive Science.<ref>{{cite web |url=http://cogsci.vassar.edu/about/index.html |title=About - Cognitive Science - Vassar College |publisher=Cogsci.vassar.edu |access-date=2012-08-15 |archive-date=17 September 2012 |archive-url=https://web.archive.org/web/20120917124231/http://cogsci.vassar.edu/about/index.html |url-status=dead }}</ref> In 1986, the first Cognitive Science Department in the world was founded at the [[University of California, San Diego]].<ref name="cogsci.ucsd.edu"/>

In the 1970s and early 1980s, as access to computers increased, [[artificial intelligence]] research expanded. Researchers such as [[Marvin Minsky]] would write computer programs in languages such as [[LISP]] to attempt to formally characterize the steps that human beings went through, for instance, in making decisions and solving problems, in the hope of better understanding human [[thought]], and also in the hope of creating artificial minds. This approach is known as "symbolic AI".

Eventually the limits of the symbolic AI research program became apparent. For instance, it seemed to be unrealistic to comprehensively list human knowledge in a form usable by a symbolic computer program. The late 80s and 90s saw the rise of [[neural networks]] and [[connectionism]] as a research paradigm. Under this point of view, often attributed to [[James McClelland (psychologist)|James McClelland]] and [[David Rumelhart]], the mind could be characterized as a set of complex associations, represented as a layered network. Critics argue that there are some phenomena which are better captured by symbolic models, and that connectionist models are often so complex as to have little explanatory power. Recently symbolic and connectionist models have been combined, making it possible to take advantage of both forms of explanation.<ref>{{cite book |first1=Artur S. |last1=d'Avila Garcez |author-link=Artur S. d'Avila Garcez |first2=Luis C. |last2=Lamb |author-link3=Dov Gabbay |first3=Dov M. |last3=Gabbay |title=Neural-Symbolic Cognitive Reasoning. Cognitive Technologies |publisher=Springer |year=2008 |isbn=978-3-540-73245-7 }}</ref><ref>{{cite book |editor1-link=Ron Sun |editor1-first=Ron |editor1-last=Sun |editor2-first=Larry |editor2-last=Bookman |title=Computational Architectures Integrating Neural and Symbolic Processes |publisher=Kluwer Academic |location=Needham, MA |year=1994 |isbn=0-7923-9517-4 }}</ref> While both connectionism and symbolic approaches have proven useful for testing various hypotheses and exploring approaches to understanding aspects of cognition and lower level brain functions, neither are biologically realistic and therefore, both suffer from a lack of neuroscientific plausibility.<ref>{{Cite web|url=http://www.encephalos.gr/48-1-01e.htm|title=Encephalos Journal|website=www.encephalos.gr|access-date=2018-02-20|archive-date=25 June 2011|archive-url=https://web.archive.org/web/20110625102426/http://www.encephalos.gr/48-1-01e.htm|url-status=live}}</ref><ref>{{Cite book|url=https://books.google.com/books?id=s-OCCwAAQBAJ&pg=PT18|title=Neural Geographies: Feminism and the Microstructure of Cognition|last=Wilson|first=Elizabeth A.|date=2016-02-04|publisher=Routledge|isbn=9781317958765|language=en|access-date=16 April 2018|archive-date=5 February 2023|archive-url=https://web.archive.org/web/20230205120513/https://books.google.com/books?id=s-OCCwAAQBAJ&pg=PT18|url-status=live}}</ref><ref>{{cite book |last1=Di Paolo |first1=Ezequiel A. |chapter=Organismically-inspired robotics: homeostatic adaptation and teleology beyond the closed sensorimotor loop |pages=19–42 |citeseerx=10.1.1.62.4813 |s2cid=15349751 |editor1-last=Murase |editor1-first=Kazuyuki |editor2-last=Asakura |editor2-first=Toshiyuki |title=Dynamic Systems Approach for Embodiment and Sociality: From Ecological Psychology to Robotics |date=2003 |publisher=Advanced Knowledge International |isbn=978-0-9751004-1-7 }}</ref><ref>{{Cite journal|last1=Zorzi |first1=Marco|last2=Testolin|first2=Alberto|last3=Stoianov|first3=Ivilin P.|date=2013-08-20 |title= Modeling language and cognition with deep unsupervised learning: a tutorial overview|journal= Frontiers in Psychology |volume=4|pages=515|doi=10.3389/fpsyg.2013.00515 |issn=1664-1078|pmc= 3747356 |pmid=23970869|doi-access=free}}</ref><ref>{{cite journal |last1=Tieszen |first1=Richard |title=Analytic and Continental Philosophy, Science, and Global Philosophy |journal=Comparative Philosophy |date=15 July 2011 |volume=2 |issue=2 |doi=10.31979/2151-6014(2011).020206 |doi-access=free }}</ref><ref>{{Cite book |url=https://books.google.com/books?id=uV9TZzOITMwC&pg=PA17 |title=Neural Network Perspectives on Cognition and Adaptive Robotics |last=Browne |first=A. |date=1997 |publisher=CRC Press |isbn=0-7503-0455-3 |language=en |access-date=16 April 2018 |archive-date=5 February 2023 |archive-url=https://web.archive.org/web/20230205120506/https://books.google.com/books?id=uV9TZzOITMwC&pg=PA17 |url-status=live }}</ref><ref>{{Cite book|url=https://books.google.com/books?id=7pPv0STSos8C&pg=PA63|title=Connectionism in Perspective|last1=Pfeifer|first1=R.|last2=Schreter|first2=Z.|last3=Fogelman-Soulié|first3=F.|last4=Steels|first4=L.|date=1989|publisher=Elsevier|isbn=0-444-59876-6|language=en|access-date=16 April 2018|archive-date=5 February 2023|archive-url=https://web.archive.org/web/20230205120506/https://books.google.com/books?id=7pPv0STSos8C&pg=PA63|url-status=live}}</ref> Connectionism has proven useful for exploring computationally how cognition emerges in development and occurs in the human brain, and has provided alternatives to strictly domain-specific / domain general approaches. For example, scientists such as Jeff Elman, Liz Bates, and Annette Karmiloff-Smith have posited that networks in the brain emerge from the dynamic interaction between them and environmental input.<ref>{{cite journal |last=Karmiloff-Smith |first=A. |year=2015 |title=An alternative to domain-general or domain-specific frameworks for theorizing about human evolution and ontogenesis |journal=AIMS Neuroscience |volume=2 |issue=2 |pages=91–104 |doi=10.3934/Neuroscience.2015.2.91 |pmid=26682283 |pmc=4678597 |doi-access=free }}</ref>

Recent developments in [[quantum computation]], including the ability to run quantum circuits on quantum computers such as [[IBM Quantum Platform]], has accelerated work using elements from quantum mechanics in cognitive models.<ref>Pothos, E. M., & Busemeyer, J. R. (2022). Quantum Cognition. Annual Review of Psychology, 73, 749–778.</ref><ref>Widdows, D., Rani, J., & Pothos, E. M. (2023). Quantum Circuit Components for Cognitive Decision-Making. Entropy, 25(4), 548.</ref>