Download Proposal for Ph.D. General Exams

Proposal for Ph.D. General Examinations
Xinyu Hugo Liu
Submitted April 13, 2004
Introduction
How can a machine represent a person as a richly social and
psychological entity? How can a machine learn deeply about a
person by reading personal narrative texts? How can these social
and psychological models be leveraged to engage and maintain an
intimate relationship with a person that is inspiring, meaningful,
and long-lasting? These questions are important if we are to build
machines that can understand, communicate, and relate to people
like another person can. Answering these questions requires giving
a machine the ability to construct socio-psychological models of a
person’s identity, culture, personality, intuition, memory, and
aesthetics, and to exploit these models to maintain subtle channels
of social communication, such as social signaling, grooming, and
empathy. My goal in the general exam is to study the areas
pertinent to representing and communicating with a person as a
socio-psychological entity.
This exam includes areas that look at humans through the
various eyes of social psychologists, cognitive AI practitioners, and
a linguists. The main area covers deep AI models of cognition that
have been proposed and built over the past 50 years. The technical
supporting area covers techniques for machine narrative
comprehension. The contextual supporting area surveys the
philosophy, sociology, and psychology of social identity.
Main Area:
Deep Computer Models of Cognition
Examiner
Pattie Maes
Associate Professor
MIT Media Laboratory
Description
The main area of this exam covers work in cognitive AI that puts
forth models of human cognition, covering various issues such as
knowledge representation, reasoning, behavior, affect, and
learning. This literature represents the various points of view of
researchers who approach AI through the lenses of multiple
representations, logic, behavior-based agents, statistical learning,
and philosophy.
Signature_______________________________Date________________
Written Requirement
The written requirement will consist of a publishable quality paper
to be graded by Professor Maes.
Reading List
Multiple representations
Marvin Minsky: 1986, The Society of Mind, New York: Simon &
Schuster. [book]
Marvin Minsky: forthcoming, The Emotion Machine. New York:
Pantheon. [link]
Marvin Minsky: 1974, A framework for representing knowledge (AI
Laboratory Memo 306). Artificial Intelligence Laboratory,
Massachusetts Institute of Technology. [link]
Randall Davis, Howard Shrobe, Peter Szolovits: 1993, “What is a
Knowledge Representation?” AI Magazine, 14(1):17-33. [link]
Tim Berners-Lee et al: 2001, “The Semantic Web” Scientific American,
May, 2001. [link]
Logic, reasoning, and planning
John McCarthy: 1958, Programs with Common Sense. Proceedings of
the Teddington Conference on the Mechanization of
Thought Processes. [link]
John McCarthy: 1990, Formalizing common sense. Norwood, NJ:
Ablex [link]
A. Newell & H. A. Simon: 1963, GPS, a program that simulates human
thought. In E. A. Feigenbaum and J. Feldman (eds.),
Computers and Thought, pages 279-293. New York:
McGraw-Hill. [?]
J. F. Lehman et al.: 1996, A gentle introduction to Soar, an architecture
for human cognition. In S. Sternberg & D. Scarborough (eds.)
Invitation to Cognitive Science (Volume 4). [link]
A. Newell: 1990, Unified Theories of Cognition, Cambridge, MA:
Harvard University Press. [book]
M. P. Georgeff et al.: 1998, The Belief-Desire-Intention Model of
Agency. In N. Jenning, J. Muller, and M. Wooldridge (eds.),
Intelligent Agents V. Springer. [link]
Stuart Russell & Peter Norvig: 2002, AI: A Modern Approach,
Prentice Hall. [book]
Martha Pollack: 1992, “The uses of plans,” AI Journal:57 [link]
Behavior-based models
Rod Brooks: 1991, “Intelligence Without Representation”, Artificial
Intelligence Journal (47), 1991, pp. 139–159. [link]
Rod Brooks: 1991, “Intelligence without Reason.” Proceedings
International Joint Conference on Artificial Intelligence '91, 569595 (1991) [link]
Rod Brooks, Cynthia Breazeal, Matthew Marjanovic, Brian
Scassellati, Matthew Williamson: 1999, "The Cog Project:
Building a Humanoid Robot" in Computation for Metaphors,
Analogy, and Agents. C. Nehaniv (ed.), Lecture Notes in
Artificial Intelligence 1562. New York, Springer, 52–87, 1999.
[link]
Rod Brooks: 2002, Flesh and Machines: How Robots Will Change Us.
Pantheon. [book]
Pattie Maes: 1994, Modeling Adaptive Autonomous Agents,
Artificial Life Journal, C. Langton, ed., Vol. 1, No. 1 & 2, MIT
Press, 1994. [link]
L. Steels: 1994, The artificial life roots of artificial intelligence.
Artificial Life Journal, Vol 1,1. MIT Press, Cambridge. [link]
Models of affect
Aaron Sloman: 1981, Why robots will have emotions. Proceedings of
the Seventh International Joint Conference on Artificial
Intelligence. [link]
A. Ortony, G.L. Clore, A. Collins: 1988, The cognitive structure of
emotions, New York: Cambridge University Press. [book]
Rosalind Picard: 1997, Affective Computing, MIT Press. [book]
Margaret Boden: 1996, Artificial Genius, Discover Magazine, 17:10.
[link]
Marvin Minsky: 1981, Jokes and the logic of the unconscious. In
Vaina and Hintikka (eds.), Cognitive Constraints on
Communication. Reidel. [link]
Learning models
L.P.
Kaelbling, L.M. Littman and A.W. Moore: 1996,
"Reinforcement learning: a survey," Journal of Artificial
Intelligence Research, vol. 4, pp. 237—285. [link]
Andrew P. Duchon, William H. Warren, and Leslie Pack Kaelbling:
1998, “Ecological Robotics,” Adaptive Behavior, Volume 6,
Number 3/4. [link]
S. Thrun and T. M. Mitchell: 1995, “Lifelong robot learning”,
Robotics and Autonomous Systems, vol. 15, pp. 24-46. [link]
Tom M. Mitchell and Sebastian B. Thrun: 1995, Learning
Analytically and Inductively. In Steier and Mitchell, editors,
Mind Matters: A Tribute to Allen Newell. Erlbaum. [link]
Case-based reasoning
C. K. Riesbeck and R. C. Schank: 1989, Inside Case-Based
Reasoning. Lawrence Erlbaum Associates, Hillsdale. [book]
Kristian Hammond, 1990: Explaining and Repairing Plans That
Fail. Artificial Intelligence 45, pp. 173-228. [?]
Leake, David B.: 1996. Case-Based Reasoning: Experiences, Lessons,
& Future Directions. Menlo Park, California: AAAI Press. [?]
Philosophy & AI
Aaron Sloman: 1996, What sort of architecture is required for a
human-like agent? Cognitive Modeling Workshop, AAAI96,
Portland Oregon, August. [link]
Aaron Sloman: 1995, A Philosophical Encounter, IJCAI. [link]
Daniel Dennett: 1992, Consciousness Explained. [book]
Margaret Boden (ed.): 1990, The Philosophy of Artificial Intelligence,
Oxford University Press, New York. [book]
Contextual Area: Building Blocks of Identity
Examiner
Judith Donath
Assistant Professor
MIT Media Laboratory
Description
My contextual supporting area looks at the issue of identity
through the broader lens of Sociology, Psychology, and Philosophy.
The readings in this area represent relevant contemporary social
theories of identity, and nominates social objects, fashion, language,
and media narratives as some of the primary building blocks for
the social composition of identity. I also examine social signaling
theory as a framework for understanding how identity is revealed
or “given off” in social communication with other people (and
machines). Through this literature I hope to attain a broader
understanding of identity – how it is perceived by ego and alter,
and what it is composed off – that will inform me in the design of
rich socio-psychological computer models of a person. Only after
we have addressed the issues of social identity can we have
sociable computers that can inspire and relate to us at a more
intuitive and intimate level.
Signature_______________________________Date________________
Written Requirement
The written requirement will consist of a publishable quality paper
to be graded by Professor Donath.
Reading List
The sociological concept of “identity”
Kurt Wolff (ed., trans.): 1950, The Sociology of Georg Simmel, Glencoe:
Free Press. [book]
D. N. Levine (ed.): 1971, On Individuality and Social Forms: Selected
Writings, University of Chicago Press, Chicago. [book]
Erving Goffman: 1959, The Presentation of Self in Everyday Life.
Doubleday: Garden City, New York. [book]
The social meanings of objects
Mihaly Csikszentmihalyi, Eugene Rochberg-Halton: 1981, The
Meaning of Things: Domestic Symbols and the Self, Cambridge
University Press, UK. [book]
David Halle: 1993, Inside Culture: Art and Class in the American
Home, University of Chicago Press, Chicago. [book]
Fashion in identity
Sarah Thornton: 1996, Club Cultures: Music, Media and Subcultural
Capital, Wesleyan University Press. [book]
Grant McCracken: 1991, Culture and Consumption: New Approaches to
the Symbolic Character of Consumer Goods and Activities,
Indiana University Press, Indiana. [book]
Fred Davis: 1994, Fashion, Culture, and Identity, University of
Chicago Press, Chicago. [book]
Sociolinguistics
George Lakoff, Mark Johnson: 1980, Metaphors We Live by.
University of Chicago Press. [book]
Peter Trudgill: 2001, Sociolinguistics: An Introduction to Language and
Society, Penguin USA. [book]
Muriel Saville-Troike: 1989, The Ethnography of Communication. New
York: Basil Blackwell. [book]
Roland Barthes: 1970, Mythologies, Paris: Seuil. [book]
Media and narratives in identity construction
Kevin Murray: 1990, Life as fiction, Ph.D. Dissertation, Department
of Psychology, University of Melbourne. [link]
Kevin Murray: 1988, The construction of identity in the narratives of
romance and comedy. In J.Shotter & K.Gergen (eds.) Texts of
Identity London: Sage. [link]
Daniel Chandler: 1998: Personal Home Pages and the Construction of
Identities
on
the
Web.
Available
at:
http://www.aber.ac.uk/media/Documents/short/webiden
t.html [link]
Debra Grodin, Thomas Lindlof (eds.): 1996, Constructing the Self in a
Mediated World, Thousand Oaks, CA: Sage. [book]
Signaling theory (how is identity given off?)
Tim Guilford, and Marian Stamp Dawkins: 1993, Receiver psychology
and the design of animal signals. Trends in the Neurosciences
16:430-436. [?]
A. Grafen: 1990a, Biological Signals as Handicaps, Journal of
Theoretical Biology, 144:517-546. [hardcopy]
T. Veblen: 1899, The Theory of the Leisure Class, New York: Dover
Publications. [book]
Technical Area:
Techniques for Narrative Comprehension
Examiner
Erik T. Mueller
Research Staff Member
IBM Thomas J. Watson Research Center
Description
This technical area covers work on machine narrative
comprehension, also known as story understanding, embedded
within the broader field of computational linguistics. As the
literature on machine narrative comprehension is quite extensive, I
give special treatment to models and techniques of comprehension
that are semantically informed, that is to say, comprehension
beyond strict parsing, and involving projection, creative inference,
and situated understanding. I also include a section on techniques
for creative narrative generation, which is a perfect complement to
comprehension in the context of person-to-person communication.
Signature_______________________________Date________________
Written Requirement
The written requirement will consist of an implementation project
and publishable quality paper to be graded by Dr. Mueller.
Reading List
Scripts, plans, goals, TAUs, plot units, and situation models for
narrative comprehension
M.G. Dyer: 1983, In-depth understanding. Cambridge, Mass.: MIT
Press. [book]
R.C. Schank & R.P. Abelson: 1977, Scripts, plans, goals, and
understanding. Hillsdale, NJ: Lawrence Erlbaum. [book]
W.G. Lehnert: 1982, Plot units: A narrative summarization strategy.
In W. G. Lehnert & M. H. Ringle (Eds.). Strategies for natural
language processing. Hillsdale, NJ: Lawrence Erlbaum
Associates. [?]
Rolf A. Zwaan & Gabriel A. Radvansky: 1998, Situation models in
language comprehension and memory. Psychological Bulletin,
123(2), 162-185. [?]
Logic-based techniques for narrative comprehension
Jerry R. Hobbs, Mark E. Stickel, Douglas Appelt, & Paul Martin:
1993, “Interpretation as abduction.” In Fernando C. N.
Pereira & Barbara J. Grosz (Eds.), Natural language processing
(pp. 69-142). Cambridge, MA: MIT [link]
Murray Shanahan: 1997, Solving the frame problem. Cambridge, MA:
MIT Press. [book]
Probabilistic and connectionist
comprehension
methods
for
narrative
Robert P. Goldman: 1990, A probabilistic approach to language
understanding (Technical Report CS-90-34). Providence, RI:
Computer Science Department, Brown University. [?]
Stefan L. Frank, Mathieu Koppen, Leo G. M. Noordman, Wietske
Vonk: 2003, Modeling knowledge-based inferences in story
comprehension. Cognitive Science, 27, 875-910. [?]
Srinivas S. Narayanan: 1997, Knowledge-based action representations
for metaphor and aspect (KARMA) (Unpublished doctoral
dissertation). University of California, Berkeley. [link]
Serendipity and explanation in creative narrative comprehension
E.A. Domeshek, 1994: “Abby: Exploring an Indexing Vocabulary
for Social Advice.” In Roger Schank, Alex Kass (eds), Inside
Case-Based Explanation. Hillsdale, NJ: Lawrence Erlbaum.
[book]
Erik Mueller: 1990, Daydreaming in humans and computers: a computer
model of stream of thought. Norwood, NJ: Ablex. [book]
David Gelernter: 1994, The Muse in the Machine: Computerizing the
Poetry of Human Thought. Free Press. [book]
Ashwin Ram: 1994, “AQUA: Questions that drive the explanation
process.” In Roger C. Schank, Alex Kass, & Christopher K.
Riesbeck (Eds.), Inside case-based explanation (pp. 207-261).
Hillsdale, NJ: Erlbaum. [link]
Creative reading
Kenneth Moorman & Ashwin Ram: 1994, A functional theory of
creative reading. The Psycgrad Journal. Technical Report GITCC-94/01, College of Computing, Georgia Institute of
Technology, Atlanta, GA, 1994. [link]
Kenneth Moorman & Ashwin Ram: 1994, Integrating creativity and
reading: A functional approach. In Sixteenth Annual
Conference of the Cognitive Science Society. [link]
Creative narrative generation
C.B. Callaway: 2000, Narrative prose generation, Ph.D. Thesis, North
Carolina State University, Raleigh, NC. [link]
Scott Turner: 1994, The Creative Process: A Computer Model of
Storytelling and Creativity. NJ: Lawrence Erlbaum. [book]