David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
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Topics in Cognitive Science 2 (4):751-770 (2010)
The study of human intelligence was once dominated by symbolic approaches, but over the last 30 years an alternative approach has arisen. Symbols and processes that operate on them are often seen today as approximate characterizations of the emergent consequences of sub- or nonsymbolic processes, and a wide range of constructs in cognitive science can be understood as emergents. These include representational constructs (units, structures, rules), architectural constructs (central executive, declarative memory), and developmental processes and outcomes (stages, sensitive periods, neurocognitive modules, developmental disorders). The greatest achievements of human cognition may be largely emergent phenomena. It remains a challenge for the future to learn more about how these greatest achievements arise and to emulate them in artificial systems.
|Keywords||History Modeling Emergence Neural networks Language Explanation Development|
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Citations of this work BETA
Axel Cleeremans (2014). Connecting Conscious and Unconscious Processing. Cognitive Science 38 (6):1286-1315.
Nick Chater, Noah Goodman, Thomas L. Griffiths, Charles Kemp, Mike Oaksford & Joshua B. Tenenbaum (2011). The Imaginary Fundamentalists: The Unshocking Truth About Bayesian Cognitive Science. Behavioral and Brain Sciences 34 (4):194-196.
Timothy T. Rogers & James L. McClelland (2014). Parallel Distributed Processing at 25: Further Explorations in the Microstructure of Cognition. Cognitive Science 38 (6):1024-1077.
Larissa K. Samuelson, Gavin W. Jenkins & John P. Spencer (2015). Grounding Cognitive‐Level Processes in Behavior: The View From Dynamic Systems Theory. Topics in Cognitive Science 7 (2):191-205.
Gary Lupyan (2013). The Difficulties of Executing Simple Algorithms: Why Brains Make Mistakes Computers Don't. Cognition 129 (3):615-636.
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