skip to content

Bulletin Archive

This archived information is dated to the 2011-12 academic year only and may no longer be current.

For currently applicable policies and information, see the current Stanford Bulletin.

Bachelor of Science in Symbolic Systems

Up one level:

Symbolic Systems

The program leading to a B.S. in Symbolic Systems provides students with a core of concepts and techniques, drawing on faculty and courses from various departments. The curriculum prepares students for advanced training in the interdisciplinary study of language and information, or for postgraduate study in any of the main contributing disciplines. It is also excellent preparation for employment immediately after graduation.

Symbolic Systems majors must complete a core of required courses plus a field of study consisting of five additional courses. All major courses are to be taken for letter grades unless an approved course is offered satisfactory/no credit only. All core courses must be passed with a grade of 'C-' or better. Students who receive a grade lower than this in a core course must alert the program of this fact so that a decision can be made about whether the student should continue in the major.

CORE REQUIREMENTS

In order to graduate with a B.S. in Symbolic Systems, a student must complete the following requirements. Some of these courses have other courses as prerequisites; students are responsible for completing each course's prerequisites before they take it. With the exception of the advanced small seminar requirement, courses cannot be used towards more than one area of the core requirements.

  1. Introductory Core Course.
    • SYMSYS 100. Introduction to Cognitive and Information Sciences
  2. Continuous Fundamentals Level 1—Single Variable Calculus (one of the following):
    • 10 units of Advanced Placement Calculus credit
    • MATH 19, MATH 20, and MATH 21. Calculus
    • MATH 41 or MATH 41A and MATH 42 or MATH 42A. Calculus (Accelerated)
  3. Continuous Fundamentals Level 2—Multivariable Calculus (one of the following):
    • CME 100. Vector Calculus for Engineers
    • CME 100A. Vector Calculus for Engineers, ACE
    • MATH 51. Linear Algebra and Differential Calculus for Several Variables
    • MATH 51A. Linear Algebra and Differential Calculus for Several Variables, ACE

    Note: MATH 52 and/or 53, or CME 102 and/or 104, are recommended and may be required for some optional higher level courses

  4. Continuous Fundamentals Level 3—Probability and Statistics (one of the following):
    • CS 109. Introduction to Probability for Computer Scientists
    • STATS 116. Theory of Probability
    • STATS 110. Statistical Methods in Engineering and the Physical Sciences
    • MS&E 120. Probabilistic Analysis
    • EE 178. Probabilistic Systems Analysis
    • MATH 151. Introduction to Probability Theory
    • CME 106/ENGR 155C. Introduction to Probability and Statistics for Engineers
  5. Discrete Fundamentals—
    1. Computer Programming (one of the following):
      • CS 106A. Programming Methodology and CS 106B. Programming Abstractions
      • CS 106X. Programming Abstractions (Accelerated)
    2. Logic and Computational Theory (one of the following):
      • CS 103. Mathematical Foundations of Computing
      • PHIL 150. Basic Concepts in Mathematical Logic
  6. Technical Depth—

    Two courses chosen from the list below, appropriate to a student's concentration (see concentration lists at http://symsys.stanford.edu/viewing/htmldocument/13607):

    Note: students concentrating in HCI, AI, or Computer Music must take CS 107.

    Area A. Computer Programming—

    • CS 107. Computer Organization and Systems

    Area B. Computational Theory—

    • CS 154. Introduction to Automata and Complexity Theory
    • CS 156. Calculus of Computation
    • CS 161. Design and Analysis of Algorithms

    Area C. Logic—

    • CS 157. Logic and Automated Reasoning
    • PHIL 151. First Order Logic
    • PHIL 152. Computability and Logic
    • PHIL 154. Modal Logic

    Area D. Decision Theory/Game Theory—

    • CS 224M. Multi-Agent Systems
    • ECON 160. Game Theory and Economic Applications
    • MS&E 236/236H. Game Theory with Engineering Applications
    • MS&E 252. Decision Analysis I: Foundations of Decision Analysis

    Area E. Probability and Statistics—

    • STATS 200. Introduction to Statistical Inference
    • CS 228. Structured Probabilistic Models: Principles and Techniques
  7. Philosophical Foundations Level 1—Introductory Philosophy (one of the following):
    • PHIL 1. Introduction to Philosophy
    • PHIL 2. Introduction to Moral Philosophy
    • PHIL 60. Introduction to Philosophy of Science
    • PHIL 102. Modern Philosophy, Descartes to Kant
    • IHUM 23A,B. The Fate of Reason
  8. Philosophical Foundations Level 2—
    • PHIL 80. Mind, Matter, and Meaning (WIM course)
  9. Philosophical Foundations Level 3—Advanced undergraduate course in metaphysics/epistemology (one of the following):
    • PHIL 162. Philosophy of Mathematics
    • PHIL 164. Central Topics in the Philosophy of Science: Theory and Evidence
    • PHIL 166. Probability: Ten Great Ideas About Chance
    • PHIL 168. Theories of Truth
    • PHIL 169. Evolution of the Social Contract
    • PHIL 180. Metaphysics
    • PHIL 180A. Realism, Anti-Realism, Irrealism, Quasi-Realism
    • PHIL 181. Philosophy of Language
    • PHIL 182. Truth
    • PHIL 184. Theory of Knowledge
    • PHIL 184B. Philosophy of the Body
    • PHIL 184F. Feminist Theories of Knowledge
    • PHIL 184P. Probability and Epistemology
    • PHIL 185. Memory
    • PHIL 186. Philosophy of Mind
    • PHIL 187. Philosophy of Action
    • PHIL 188. Personal Identity
    • PHIL 189. Examples of Free Will
  10. Cognition and Neuroscience—
    1. PSYCH 55. Introduction to Cognition and the Brain
    2. An additional undergraduate course in cognition and/or neurosciences (one of the following):
      • BIO 20. Introduction to Brain and Behavior
      • PSYCH 30. Introduction to Perception
      • PSYCH 45. Introduction to Learning and Memory
      • PSYCH 50. Introduction to Cognitive Neuroscience
      • PSYCH 60. Introduction to Developmental Psychology
      • PSYCH 70. Introduction to Social Psychology
      • PSYCH 131. Language and Thought
      • PSYCH 133. Human Cognitive Abilities
      • PSYCH 141. Cognitive Development
      • PSYCH 154. Judgement and Decision Making
  11. Natural Language—
    1. Language and Mind (one of the following):
      • LINGUIST 1. Introduction to Linguistics
      • LINGUIST 106. Introduction to Speech Perception
      • LINGUIST 140. Language Acquisition I
      • PSYCH 131. Language and Thought
    2. Linguistic Theory (one of the following):
      • LINGUIST 110. Introduction to Phonetics and Phonology
      • LINGUIST 120. Introduction to Syntax
      • LINGUIST 130A/230A. Introduction to Semantics and Pragmatics
  12. Computation and Cognition—A course applying core technical skills to cognition (one of the following):
    • BIOE 341. Computational Neural Networks
    • CS 121. Introduction to Artificial Intelligence
    • CS 221. Artificial Intelligence: Principles and Techniques
    • CS 222. Rational Agency and Intelligent Interaction
    • CS 224M. Multi-Agent Systems
    • CS 227. Knowledge Representation and Reasoning
    • CS 228. Probabilistic Graphical Models: Principles and Techniques
    • CS 229. Machine Learning
    • LINGUIST 180/CS 124. From Languages to Information
    • LINGUIST 182. Computational Theories of Syntax
    • PSYCH 204. Computation and Cognition: the Probabilistic Approach
    • PSYCH 209A. The Neural Basis of Cognition: A Parallel Distributed Processing Approach
    • PSYCH 239. Formal and Computational Approaches in Psychology and Cognitive Science
  13. Advanced Small Seminar Requirement

    An upper-division, limited-enrollment seminar drawing on material from other courses in the core. Courses listed under Symbolic Systems Program offerings with numbers from SYMSYS 200 through 209 are acceptable, as are other courses which are announced at the beginning of each academic year. A course taken to fulfill this requirement can also be counted toward another requirement, as part of either the core or a student's concentration (see below), but not both.

FIELDS OF STUDY

In addition to the core requirements listed above, the Symbolic Systems major requires each student to complete a field of study consisting of five courses that are thematically related to each other. Students select concentrations from the list below or design others in consultation with their advisers. The field of study is declared on Axess; it appears on the transcript but not on the diploma.

UNDERGRADUATE RESEARCH

The program strongly encourages all SSP majors to gain experience in directed research by participating in faculty research projects or by pursuing independent study. In addition to the Symbolic Systems Honors Program (see below), the following avenues are offered.

  1. Summer Internships: students work on SSP-related faculty research projects. Application procedures are announced in the winter quarter for SSP majors.
  2. Research Assistantships: other opportunities to work on faculty research projects are typically announced to SSP majors as they arise during the academic year.
  3. Independent Study: under faculty supervision. For course credit, students should enroll in SYMSYS 196.

Contact SSP for more information on any of these possibilities, or see http://symsys.stanford.edu. In addition, the Undergraduate Advising and Research office offers grants and scholarships supporting student research projects at all levels; see http://ual.stanford.edu/OO/research_opps/Grants.

HONORS PROGRAM

Seniors in SSP may apply for admission to the Symbolic Systems honors program prior to the beginning of their final year of study. Students who are accepted into the honors program can graduate with honors by completing an honors thesis under the supervision of a faculty member. Course credit for the honors project may be obtained by registering for SYMSYS 190, Honors Tutorial, for any quarters while a student is working on an honors project. Juniors who are interested in doing an honors project during their senior year are advised to take SYMSYS 200, Symbolic Systems in Practice. SYMSYS 191, Senior Honors Seminar, is recommended for honors students during the senior year. Contact SSP or visit the program's web site for more information on the honors program, including deadlines and policies.

COGNATE COURSES

The following is a list of cognate courses that may be applied to the B.S. in Symbolic Systems. See respective department listings for course descriptions and General Education Requirements (GER) information.

© Stanford University - Office of the Registrar. Archive of the Stanford Bulletin 2011-12. Terms of Use | Copyright Complaints