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This archived information is dated to the 2009-10 academic year only and may no longer be current.

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Symbolic Systems

Director: Kenneth Taylor

Director of Graduate Studies: Christopher Manning

Associate Director: Todd Davies

Program Committee: Lera Boroditsky, Herbert Clark, Todd Davies, Daniel Jurafsky, Scott Klemmer, Daphne Koller, Krista Lawlor, Christopher Manning, James McClelland, Clifford Nass, Stanley Peters, Christopher Potts, Eric Roberts, Ivan A. Sag, Kenneth A. Taylor, Johan van Benthem, Thomas A. Wasow, Terry Winograd

Program Faculty:

Art and Art History: Scott Bukatman (Associate Professor)

Applied Physics: Bernardo Huberman (Consulting Professor)

Classics: Reviel Netz (Professor)

Civil and Environmental Engineering: John Kunz (Lecturer)

Communication: Jeremy Bailenson (Assistant Professor), Clifford J. Nass (Professor), Byron Reeves (Professor), Frederick Turner (Assistant Professor)

Computer Science: David Dill (Professor), Michael Genesereth (Associate Professor), Jeffrey Heer (Assistant Professor), Oussama Khatib (Professor), Scott Klemmer (Assistant Professor), Daphne Koller (Professor), Jean-Claude Latombe (Professor), Marc Levoy (Professor), Christopher Manning (Associate Professor), John McCarthy (Professor, emeritus), Andrew Ng (Associate Professor), Nils Nilsson (Professor, emeritus), Vaughan Pratt (Professor, emeritus), Eric Roberts (Professor, Teaching), Tim Roughgarden (Assistant Professor), Mehran Sahami (Associate Professor, Teaching), Sebastian Thrun (Professor), Terry Winograd (Professor)

Economics: Muriel Niederle (Associate Professor)

Education: Raymond P. McDermott (Professor), Roy Pea (Professor), Daniel Schwartz (Professor)

Electrical Engineering: Krishna Shenoy (Associate Professor)

French and Italian: Jean-Pierre Dupuy (Professor)

Genetics: Russ B. Altman (Professor)

Graduate School of Business: Baba Shiv (Professor)

History: Jessica G. Riskin (Associate Professor)

Linguistics: Arto Anttila (Associate Professor), Joan Bresnan (Professor, emerita), Eve Clark (Professor), Daniel Jurafsky (Associate Professor), Ronald Kaplan (Consulting Professor), Lauri Karttunen (Consulting Professor), Martin Kay (Professor), Beth Levin (Professor), Christopher Manning (Associate Professor), Stanley Peters (Professor, emeritus), Ivan A. Sag (Professor), Meghan Sumner (Assistant Professor), Thomas A. Wasow (Professor), Annie Zaenen (Consulting Professor)

Management Science and Engineering: Pamela Hinds (Associate Professor)

Mathematics: Keith Devlin (Consulting Professor), Persi Diaconis (Professor), Solomon Feferman (Professor, emeritus)

Medicine: Russ B. Altman (Professor), Mark Musen (Professor)

Music: Jonathan Berger (Professor), Christopher Chafe (Professor), Eleanor Selfridge-Field (Consulting Professor), Ge Wang (Assistant Professor)

Neurobiology: Ben Barres (Professor), William T. Newsome (Professor), Jennifer Raymond (Associate Professor)

Philosophy: Michael Bratman (Professor), Alexis Burgess (Assistant Professor), Mark Crimmins (Associate Professor), John Etchemendy (Professor), Solomon Feferman (Professor, emeritus), Dagfinn Føllesdal (Professor), Krista Lawlor (Associate Professor), Grigori Mints (Professor), Marc Pauly (Assistant Professor), John Perry (Professor, emeritus), Brian Skryms (Professor), Kenneth Taylor (Professor), Johan van Benthem (Professor), Thomas A. Wasow (Professor)

Psychiatry and Behavioral Sciences: Vinod Menon (Associate Professor, Research)

Psychology: Lera Boroditsky (Assistant Professor), Herbert H. Clark (Professor), Anne Fernald (Associate Professor), Brian Knutson (Associate Professor), Ellen Markman (Professor), James McClelland (Professor), Samuel McClure (Assistant Professor), Michael Ramscar (Assistant Professor), Barbara Tversky (Professor, emerita), Anthony Wagner (Associate Professor), Brian Wandell (Professor)

Statistics: Persi Diaconis (Professor), Susan P. Holmes (Professor, Teaching)

Symbolic Systems: Todd Davies (Lecturer), Tracy King (Consulting Associate Professor), Jeff Shrager (Consulting Associate Professor), Paul Skokowski (Consulting Associate Professor)

Other Affiliates: David Barker-Plummer (CSLI Engineering Research Associate), Daniel Flickinger (CSLI Senior Research Engineer), Stephan Oepen (CSLI Senior Research Engineer)

Program Offices: Margaret Jacks Hall, Building 460, Suite 040

Mail Code: 94305-2150

Phone: (650) 723-4284

Email: symsys-afs@lists.stanford.edu

Web Site: http://symsys.stanford.edu

Courses offered by the Program in Symbolic Systems are listed under the subject code SYMSYS on the Stanford Bulletin's ExploreCourses web site.

The observation that both human beings and computers can manipulate symbols lies at the heart of Symbolic Systems, an interdisciplinary program focusing on the relationship between natural and artificial systems that represent, process, and act on information. Computer programs, natural languages, the human mind, and the Internet embody concepts whose study forms the core of the Symbolic Systems curriculum, such as computation, representation, communication, and intelligence. A body of knowledge and theory has developed around these notions, from disciplines such as philosophy, computer science, linguistics, psychology, statistics, neurobiology, and communication. Since the invention of computers, researchers have been working across these disciplines to study questions such as: in what ways are computers and computer languages like human beings and their languages; how can the interaction between people and computers be made easier and more beneficial?

The core requirements of the Symbolic Systems Program (SSP) include courses in symbolic logic, the philosophy of mind, formal linguistics, cognitive psychology, programming, the mathematics of computation, statistical theory, artificial intelligence, and interdisciplinary approaches to cognitive science. These courses prepare students with the vocabulary, theoretical background, and technical skills needed for study and research at the advanced undergraduate and graduate levels. Most of the courses in SSP are drawn from affiliated departments. Courses designed specifically for the program are aimed at integrating and supplementing topics covered by the department-based offerings. The curriculum includes humanistic approaches to questions about language and intelligence, as well as training in science and engineering.

SSP offers B.S. and M.S. degree programs. Both programs require students to master a common core of required courses and to choose an area of specialization.

Mission of the Undergraduate Program in Symbolic Systems

The undergraduate program in Symbolic Systems is an interdisciplinary program focusing on the relationship between natural and artificial systems that represent, process, and act on information. The mission of the program is to prepare majors with the vocabulary, theoretical background, and technical skills necessary to research questions about language, information, and intelligence, both human and machine. The curriculum offers a combination of traditional humanistic approaches to these questions as well as a training and familiarity with contemporary developments in the science and technology of computation. Students in the major take courses in cognitive science, computer programming, computational theory, probability, cognitive psychology, linguistics, and artificial intelligence. The program prepares student for careers in corporate and private sectors as well as for further study in graduate school.

LEARNING OUTCOMES

The program expects its undergraduate majors to be able to demonstrate the following learning outcomes. These learning outcomes are used in evaluating students and the Symbolic Systems Program . Students are expected to demonstrate:

  1. understanding of important concepts from the undergraduate core requirements.
  2. ability to apply core concepts to an advanced problem area.
  3. ability to apply concepts and methods from more than one discipline to a particular issue.
  4. ability to think critically about advanced reading material.
  5. ability to present a cogent, coherent, evidence-backed argument.

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