<--- Back to Details
First PageDocument Content
Knowledge / Aaron Sloman / POP-11 / Cybernetics / Applications of artificial intelligence / .ai / Ai / Computer science / Strong AI / Artificial intelligence / Science / Computational neuroscience
Date: 2011-08-27 17:10:57
Knowledge
Aaron Sloman
POP-11
Cybernetics
Applications of artificial intelligence
.ai
Ai
Computer science
Strong AI
Artificial intelligence
Science
Computational neuroscience

Add to Reading List

Source URL: www.cs.bham.ac.uk

Download Document from Source Website

File Size: 78,07 KB

Share Document on Facebook

Similar Documents

Risks and mitigation strategies for Oracle AI Abstract: There is no strong reason to believe human level intelligence represents an upper limit of the capacity of artificial intelligence, should it be realized. This pose

DocID: 1rOi4 - View Document

Artificial intelligence / Computational neuroscience / Futurology / Technology / Time / Future / Singularitarianism / Philosophy of artificial intelligence / Superintelligence / Artificial general intelligence / Strong AI / Ai

The Data You Have... Tomorrow’s Information Business Marjorie M.K. Hlava President Access Innovations, Inc

DocID: 1nFdt - View Document

Future / Artificial intelligence / Futurology / Transhumanists / Computational neuroscience / Friendly artificial intelligence / Eliezer Yudkowsky / Strong AI / Agent-based model / Singularitarianism / Science / Time

Aligning Superintelligence with Human Interests: An Annotated Bibliography Nate Soares Machine Intelligence Research Institute

DocID: 1gGhe - View Document

Neuropsychology / Behavioural sciences / Philosophy of mind / Mental processes / Cognitive neuroscience / Psychology / Strong AI / Emotion / Consciousness / Mind / Cognitive science / Ethology

Microsoft Word - P583_584_CNT_14_45__KOKORO_IDX.doc

DocID: 1gvAC - View Document

Actuarial science / Exponentials / Bayesian statistics / Probability theory / Pareto distribution / Socioeconomics / Strong AI / Normal distribution / Stable distribution / Statistics / Probability and statistics / Probability

Predicting AGI: What can we say when we know so little? Fallenstein, Benja Mennen, Alex

DocID: 1gsMG - View Document