Cognitive Science and Machine Learning Summer School (MLSS), Sardinia 2010
Cognitive science aims to reverse engineer human intelligence; machine learning provides one of our most powerful sources of insight into how machine intelligence is possible. Cognitive science therefore raises challenges for, and draws inspiration from, machine learning; and insights about the human mind may help inspire new directions for machine learning. This summer school brings together leading researchers from both fields, and those working at the interface between them. It is aimed at graduate students, post-docs and established researchers from both the cognitive science and machine learning communities, interested in exploring the interface between human and machine intelligence.
More about the event at http://www.mlss.cc/sardinia10
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The typical analysis of cognitive science spans many levels of organization, from learning and decision to logic and planning; from neural circuitry to modular brain organization. The fundamental concept of cognitive science is that "thinking can best be understood in terms of representational structures in the mind and computational procedures that operate on those structures." <a href="https://liteblue.me">liteblue</a>
The typical analysis of cognitive science spans many levels of organization, from learning and decision to logic and planning; from neural circuitry to modular brain organization. The fundamental concept of cognitive science is that "thinking can best be understood in terms of representational structures in the mind and computational procedures that operate on those structures.
The typical analysis of cognitive science spans many levels of organization, from learning and decision to logic and planning; from neural circuitry to modular brain organization. The fundamental concept of cognitive science is that "thinking can best be understood in terms of representational structures in the mind and computational procedures that operate on those structures.
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Mental science consequently raises difficulties for, and draws motivation from, AI; and bits of knowledge about the human brain might assist with rousing new headings for AI.
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