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ELL457: Special Topics in Cognitive and Intelligent Systems

HUL381: Mind, Machines and Language

If you are doing the course, please join the Piazza forum (the access code has been announced in class).

This will be a Cognitive Science course with a focus on language. We will talk about how the human mind learns and processes language, how we can get machines (computers) to learn and process language, and what the connections are between the two: what can our computational models of language tell us about how the mind itself represents, produces, and comprehends language?

Instructors: Rajakrishnan Rajkumar and Sumeet Agarwal
TAs: Deepshikha and Vaibhav Grover
3 credits (3-0-0)
II Semester 2015–16
M Th 17:00–18:20, LH 619

Evaluation components

References

  1. Jay Friedenberg and Gordon Silverman. Cognitive Science: An Introduction to the Study of Mind. SAGE Publications, 2006.
  2. José Luis Bermúdez. Cognitive Science: An Introduction to the Science of the Mind. Cambridge, 2010.
  3. David Buss. Evolutionary Psychology: The New Science of the Mind. Pearson, 2014.
  4. Lance Workman and Will Reader. Evolutionary Psychology: An Introduction. Cambridge, 2014.
  5. Turing, Alan M. Computing Machinery and Intelligence. Mind LIX(236): 433–460 (1950) [doi:10.1093/mind/LIX.236.433] [pdf] [sqapo].
  6. Searle, John R. Minds, Brains, and Programs. Behavioral and Brain Sciences 3: 417–424 (1980) [doi:10.1017/S0140525X00005756] [pdf].
  7. Pinker, Steven. How the Mind Works. Penguin, 1999.
  8. Fodor, Jerry. The Mind Doesn't Work That Way: The Scope and Limits of Computational Psychology. MIT, 2000.
  9. Thomas L. Griffiths, Charles Kemp, and Joshua B. Tenenbaum. Bayesian models of cognition. In Ron Sun (ed.), The Cambridge handbook of computational cognitive modeling (2008) [pdf].
  10. George Lakoff and Mark Johnson. Metaphors We Live By. Chicago, 1980.
  11. Matthew J. Traxler. Introduction to Psycholinguistics: Understanding Language Science. Wiley-Blackwell, 2011.

Planned schedule

Serial no. Lecture nos. Topics Instructor Slides/Links
1 1–4 Introduction; Philosophical, Psychological, and Cognitive approaches to understanding the mind RR, SA Introduction: Philosophical and Psychological Perspectives
2 5–10 Language and the Brain; Evolutionary Psychology RR, SA, Stephen Stich Brain and Language
3 11–12; 18–23 Nature of intelligence and thinking machines (Turing, Searle, Pinker) RR, SA Thinking Machines, Sentence memory exercise, Searle's Chinese room
4 13–18 Words: Morphology, spoken word comprehension (TRACE) RR Word Processing, Jabberwocky
5 24–25 Computational theories and models of mind: Classical, Connectionist, Bayesian SA Computational Models of Mind
6 26 Words: Markov models, Zipf's law SA Zipf's law; The brain dictionary (video, interactive 3D viewer, paper); Markov Model examples
7 27–28 Non-literal language processing; metaphor and embodiment RR, SA Metaphor and Embodiment; Non-Literal Language Processing

[Image credits: directactioneverywhere.com; mcgill.ca; edx.org; wikipedia.org; nu.ac.th; binghamton.edu.]

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