Schedule
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Date
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Subject
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Instructor
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Homework
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Required |
Supplemental Readings
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| Th 9/4 |
Introduction Minds can be modeled at different levels; Cogntivie science crosses these levels (ppt) |
Richards Ungar |
Encyclopedia of Cognitive Science. "What is Cognitive Science" | ||
| Tu 9/9 |
What is intelligence? The Turing test tries to answer the question "Could a computer be intelligent?" The world is exponentially complex |
Ungar | Homework 1 due 9/16 at 1:30 | Turing "Computing machinery & intelligence" Mind 59:433-460 | Clark Mindware Chapter 1, Loebner (Turing) competition more on the turing test |
| Th 9/11 |
Kinds of minds Philosophers abstractly characterize minds using functionality and
intentionality |
Ungar | Nagel "What is it like to be a bat?" Chalmers "The Puzzle of Conscious Experience" | ||
| Tu 9/16 |
Voles in Love Complex emotions linke love can have simple biological bases (ppt) |
Ungar
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| Th 9/18 |
How do brains work? The brain is composed
of modulates with networks of neurons that compute and learn |
Ungar |
Homework
2 due 9/25/07 at 1pm
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Kandel et al. Essentials of Neural Science Chapter
2: Nerve Cells |
Rumelhardt. Chapter 1:
"The Appeal of Parallel Distributed Processing." Invariant visual representation by single neurons in the human brain, R. Quian Quiroga et. al. |
| Tu 9/23 |
Computers vs. Brains Brains don't work like (classic von Neuman) computers, even through they can be modeled by them(ppt) |
Ungar |
Davis The Universal Computer Chapter 7 Markus Kludge, chapter 1
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Turing Machines and the Church-Turing Thesis
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| Th 9/25 |
Perception I: You don't see what is in the world; how do we study this?(ppt) |
Richards | (pgs 35-49) |
David
Marr, Vision Reisenberg, Cognition, Chapter 2 (pg 1-34) |
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| Tu 9/30 |
Perception II: |
Richards |
Homework 3 due 10/7 at 1:30 |
Kandel et al. Principles of Neural Science Chapter 21: "Construction of the Visual Image" | Moore, Introduction to Hearing. TDS Appendix and elephant digression |
| Tr 10/2 |
Perception III "What" we see and "where" we see it -- separate
visual pathways? |
Richards |
Branich, Cognitive Neuro-science and Neuropsychology, Ch 6 (part 1 and part 2 pgs 185-200) & 7 (part 1 and part 2; pages 222-234; 243-249)
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| Tu 10/7 |
Development and Plasticity Ferrets and Barn Owls; brains rewire themselvs based on experience
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Richards |
Homework 3 and solutions Blackboard |
vonMelchner et al., "visual behavior auditory pathway," Nature, 2000 (pdf) Knudsen, "instructed learning in the auditory localizatoin pathwy of the barn owl," Nature, 2002 (pdf) |
Sharma et al, "induction of auditoyr cortex," Nature (pdf) |
| Th 10/9 |
Learning and memory Different parts of the brain do different kinds of learning: Working memory is transferred to semantic memory in the cortex via the hippocampus All share neuronal mechanisms with sea slugs |
Ungar | Encyclopedia of Cognitive Science articles: "Neural basis of Memory"; "Memory consolidation"; "Memory distortions" | Bower. A brief History of Memory Research. Encyclopedia: Learning and memory; Working memory | |
| Tu 10/14 | FALL BREAK |
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| W 10/15 | midterm 1 review | Richards Ungar | 5:00 pm B3 Meyerson Hall |
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Th 10/16 |
MIDTERM 1
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solns | |||
| Tu 10/21 |
Reinforcement Learning Reinforcement learning is widely used in animals, humans, and robots
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Ungar | Lieberman. Chapter 4: "Theories of conditioning and the missing two pages" Sutton and Barto. Reinforcement Learning. Chapter 1 | Kalat. Chapter 13: "The biology of learning and memory". Tesauro's TDGammon. | |
| Th 10/23 |
Probabilistic reasoning: Bayes Rule Bayes Rule describes optimal reasoning under uncertainty |
Ungar | Homework
4
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Conditional Probability pgs 57-71 |
Bayes' Theorem
tutorial E. Yudkowsky's An Intuitive Explanation of Bayesian Reasoning Mitchell. Machine Learning. pp 154-159, 177-184 & additional pages |
| Tu 10/28 |
Judgement and Decision Making I People use sub-optimal heuristics when making decisions |
Richards |
Reisberg, Ch 13
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| Th 10/30 |
Judgement and Decision Making II How to understand human decision making -- framing effects etc.
(ppt)
Attention and Executive Function |
Richards | Homework
4 and solutions.
Blackboard. |
Tversky et al, Judgement under uncertainty: heuristics and biases Chapter 10
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Gigerenzer, "Ecological Intelligence in the evolution of the mind," by Cummins and Allen Chapter 1
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| Tu 11/4 |
Probabilistic models of mind: category learning, vision and speech Bayes rule describes many types of thought including vision, speech recognition and category learning. THIS LECTURE WAS NOT GIVEN (ppt) |
Ungar | Report Proposal -- title abstract and seed reference | example (corrected version!) and some advice |
Tennenbaum and Griffiths"Bayesian modeling of human concept learning" |
| Th 11/6 |
Language The words (semantics) and rules (syntax) of
language are processed by differnet parts of the brain |
Richards Ungar | Homework
5 and solutions.
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Speech Recognition pgs 568-577 |
Ullman. Neurocognitive Perspective on Language. Nature Neuroscience. Fosler-Lussier. Markov models and hidden markov models: a brief tutorial. |
| Tu 11/11 |
Why computers are autistic Theory of mind is subtle. Simulation helps understand the world
and other people. |
Ungar | Homework 5 and solution (later!) |
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| Th 11/13 |
Metaphor and simulation Thought is multi-modal and embodied. Mirror neurons simulation
grasping actions |
Ungar
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Gallese, Vittorio. A Neuro-scientific Grasp of Concepts (2003) & The Inner Sense of Action. (2000) | |
| Tu 11/18 |
Attention and executive function We process relatively little information impinging on our sense
organs. How does the brain choose what to process? |
Richards |
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Kandel et al. Principles of Neural Science. Chapter 19: "Cognition and the cortex" |
Crick. Chapter 20: "Certain
aspects of the cerebral cortex". Sejnowski. Chapter 21: Branich, Cognitive Neuroscience and Neuropsychology, Chapter 11 |
| Tu 11/20 |
Emotion Emotions as interpretations of physiological states |
Ungar | Homework
6 due 12/2/08 at 1:30 Blackboard |
Ch 13; Emotion. In Cog. Neuroscience, Gazzaniga et al.Cornelius. Chapter 13 I & II |
Emotion and the Human Brain MITECS. Rolls. 'Précis of "The Brain and Emotion"' Behavioral and Brain Science. |
| Thur 11/25 |
Consciousness Human awareness seems to derive from a winner-take-all
competition among many subconscious neural assemblies |
Ungar | Koch, The Quest for Consciousness, ch14 | ||
| Th 11/27 | THANKSGIVING BREAK |
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| Tu 12/2 |
Course Summary |
Ungar | |||
| Wed 12/3 | Review Session | Richards Ungar |
5:00 pm. B3 Meyerson | ||
| Th 12/4 | MIDTERM 2 |
Exam 2 covers: Oct. 21-Nov 25, inclusive. |
Practice exam and its |
a brief summary of some concepts we have covered | |
| Th 12/11 |
Report drop off |