A Standard Model of the Mind: Toward a Common Computational Framework across Artificial Intelligence, Cognitive Science, Neuroscience, and Robotics (bibtex)
by Laird, John E., Lebiere, Christian and Rosenbloom, Paul S.
Abstract:
The purpose of this article is to begin the process of engaging the international research community in developing what can be called a standard model of the mind, where the mind we have in mind here is human-like. The notion of a standard model has its roots in physics, where over more than a half-century the international community has developed and tested a standard model that combines much of what is known about particles. This model is assumed to be internally consistent, yet still have major gaps. Its function is to serve as a cumulative reference point for the field while also driving efforts to both extend and break it.
Reference:
A Standard Model of the Mind: Toward a Common Computational Framework across Artificial Intelligence, Cognitive Science, Neuroscience, and Robotics (Laird, John E., Lebiere, Christian and Rosenbloom, Paul S.), In AI Magazine, volume 38, 2017.
Bibtex Entry:
@article{laird_standard_2017,
	title = {A {Standard} {Model} of the {Mind}: {Toward} a {Common} {Computational} {Framework} across {Artificial} {Intelligence}, {Cognitive} {Science}, {Neuroscience}, and {Robotics}},
	volume = {38},
	issn = {0738-4602, 0738-4602},
	url = {https://search.proquest.com/docview/1987347010?pq-origsite=gscholar},
	doi = {10.1609/aimag.v38i4.2744},
	abstract = {The purpose of this article is to begin the process of engaging the international research community in developing what can be called a standard model of the mind, where the mind we have in mind here is human-like. The notion of a standard model has its roots in physics, where over more than a half-century the international community has developed and tested a standard model that combines much of what is known about particles. This model is assumed to be internally consistent, yet still have major gaps. Its function is to serve as a cumulative reference point for the field while also driving efforts to both extend and break it.},
	number = {4},
	journal = {AI Magazine},
	author = {Laird, John E. and Lebiere, Christian and Rosenbloom, Paul S.},
	month = dec,
	year = {2017},
	keywords = {Virtual Humans, UARC},
	pages = {13}
}
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