Accompanying Readings: Chapter 1
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Four assignments (60%)
Final project
Week | Reading | Topic | Assignments |
---|---|---|---|
Jan 4 | Chpt 1 | Introduction | |
Jan 8, 11 | Chpt 2,4 | Neurons, Population Representation | #1 posted |
Jan 15, 18 | Chpt 4 | Temporal Representation | |
Jan 22, 25, 29 | Chpt 5,6 | Feedforward Transformations | #1 due (22rd at midnight); #2 posted |
Feb 1, 5, 8 | Chpt 6,8 | Dynamics | |
Feb 12, 15 | Chpt 7 | Analysis of Representations | #2 due (17th at midnight); #3 posted |
Feb 19, 22 | *Reading Week* | ||
Feb 26, Mar 1 | Provided | Symbols | |
Mar 5 | Chpt 8 | Memory | #3 due (5th at midnight) |
Mar 8, 12, 15 | Provided | Ongoing Research | #4 due (12th at midnight) |
Mar 19, 22 | Chpt 9 | Action Selection and Learning | |
Mar 26 | Conclusion | ||
Mar 29, Apr 2 | Project Presentations |
Lack of function or behaviour
Assumes canonical algorithm repeats
Expects intelligence to 'emerge'
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from IPython.display import HTML
HTML('<H2>A Neuron</H2><p><iframe src="https://rawgit.com/celiasmith/syde556/master/lecture1/neuron.html" width=825 height=475></iframe>')
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Use calcium to glow when Ca2+ ions bond
Good spatial and good temporal resolution
E.g. In a fish embryo
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Lots of details
Hard to get a big picture
"Data-rich and theory-poor" (Churchland & Sejnowski, 1994; still true)
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