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This archived information is dated to the 2010-11 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

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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 six 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.

  1. Cognitive Science: SYMSYS 100. Introduction to Cognitive and Information Sciences
  2. Computer Programming:
    1. CS 106A. Programming Methodology and 106B. Programming Abstractions; or 106X. Programming Methodology and Abstractions (Accelerated); and
    2. CS 107. Computer Organization and Systems
  3. Logic:
    1. PHIL 150. Basic Concepts in Mathematical Logic
    2. PHIL 151. First-Order Logic
  4. Computational Theory:
    1. CS 103. Mathematical Foundations of Computing
  5. Probability: one of the following:

    CS 109. Introduction to Probability for Computer Scientists

    CME 106/ENGR 155C. Introduction to Probability and Statistics for Engineers

    EE 178. Probabilistic Systems Analysis

    MATH 151. Introduction to Probability Theory

    MS&E 120. Probabilistic Analysis

    STATS 110. Statistical Methods in Engineering and the Physical Sciences

    STATS 116. Theory of Probability

  6. Philosophical Foundations:
    1. an introductory course in Philosophy must be taken prior to the required PHIL 80, from among the following:

    PHIL 10. God, Self, and World: An Introduction to Philosophy

    PHIL 20. Introduction to Moral Philosophy

    PHIL 30. Introduction to Political Philosophy

    PHIL 60. Introduction to Philosophy of Science

    PHIL 102. Modern Philosophy, Descartes to Kant

    IHUM 23A,B. The Fate of Reason

    and

    1. PHIL 80. Mind, Matter, and Meaning (WIM)
  7. Cognitive Psychology: PSYCH 55. Introduction to Cognition and the Brain
  8. Language and Mind: one of the following:

    LINGUIST 1. Introduction to Linguistics

    LINGUIST 140. Language Acquisition I

    PHIL 181. Philosophy of Language

    PSYCH 131. Language and Thought

    PSYCH 137. Birds to Words: Cognition, Communication, and Language

  9. Linguistic Theory: one of the following:

    LINGUIST 120. Introduction to Syntax

    LINGUIST 130A. Introduction to Linguistic Meaning

    LINGUIST 180. From Languages to Information

    LINGUIST 230A. Introduction to Semantics and Pragmatics

  10. Artificial Intelligence: CS 121. Introduction to Artificial Intelligence, or 221. Artificial Intelligence: Principles and Techniques
  11. Advanced Small Seminar:* 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 one of these requirements 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 six 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.

Applied Logic

Artificial Intelligence

Cognitive Science

Computer Music

Decision Making and Rationality

Human-Computer Interaction

Learning

Natural Language

Neurosciences

Philosophical Foundations

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.

BIO 20. Introduction to Brain and Behavior (Same as HUMBIO 21)

BIO 150/250. Human Behavioral Biology (Same as HUMBIO 160)

BIO 153. Cellular Neuroscience: Cell Signaling and Behavior

CME 106. Introduction to Probability and Statistics for Engineers (Same as ENGR 155C)

COMM 106/206. Communication Research Methods

COMM 169/269. Computers and Interfaces

COMM 172/272. Media Psychology

CS 21N. Can Machines Know? Can Machines Feel?

CS 26N. Motion Planning for Robots, Digital Actors, and Other Moving Objects

CS 47N. Computers and the Open Society

CS 51N. Visionaries in Computer Science

CS 74N. Digital Dilemmas

CS 103. Mathematical Foundations of Computing

CS 103A. Discrete Mathematics for Computer Science

CS 103B. Discrete Structures

CS 103X. Discrete Structures (Accelerated)

CS 106A. Programming Methodology (Same as ENGR 70A)

CS 106B. Programming Abstractions (Same as ENGR 70B)

CS 106X. Programming Abstractions (Accelerated) (Same as ENGR 70X)

CS 107. Computer Organization and Systems

CS 108. Object-Oriented Systems Design

CS 109. Introduction to Probability for Computer Scientists

CS 110. Principles of Computer Systems

CS 121. Introduction to Artificial Intelligence

CS 124. From Languages to Information (Same as LINGUIST 180/280)

CS 142. Web Applications

CS 147. Introduction to Human-Computer Interaction Design

CS 148. Introductory Computer Graphics and Imaging

CS 154. Introduction to Automata and Complexity Theory

CS 157. Logic and Automated Reasoning

CS 161. Design and Analysis of Algorithms

CS 170. Composition, Coding, and Performance with SLOrc (Same as MUSIC 128)

CS 181. Computers, Ethics, and Public Policy

CS 193D. Professional Software Development with C++

CS 193S. Scalable Web 2.0 Programming

CS 204. Computational Law

CS 205A. Mathematical Methods for Robotics, Vision, and Graphics

CS 207. The Economics of Software

CS 208. The Canon of Computer Science

CS 221. Artificial Intelligence: Principles and Techniques

CS 222. Rational Agency and Intelligent Interaction (Same as PHIL 358)

CS 223A. Introduction to Robotics

CS 223B. Introduction to Computer Vision

CS 224M. Multi-Agent Systems

CS 224N. Natural Language Processing (Same as LINGUIST 284)

CS 224S. Speech Recognition and Synthesis (Same as LINGUIST 285)

CS 224U. Natural Language Understanding (Same as LINGUIST 188/288)

CS 227. Reasoning Methods in Artificial Intelligence

CS 228. Structured Probabilistic Models: Principles and Techniques

CS 228T. Structured Probabilistic Models: Theoretical Foundations

CS 229. Machine Learning

CS 247. Human-Computer Interaction Design Studio

CS 249A. Object-Oriented Programming from a Modeling and Simulation Perspective

CS 276. Information Retrieval and Web Search (Same as LINGUIST 286)

CS 303. Designing Computer Science Experiments

CS 376. Research Topics in Human-Computer Interaction

CS 377. Topic in Human-Computer Interaction

CS 377L. Learning in a Networked World (Same as EDUC 298)

CS 378. Phenomenological Foundations of Cognition, Language, and Computation

CS 547. Human-Computer Interaction Seminar

ECON 51. Economic Analysis II

ECON 137. Information and Incentives

ECON 160. Game Theory and Economic Applications

EDUC 218. Topics in Cognition and Learning: Play

EDUC 298. Learning in a Networked World (Same as CS 377L)

EE 178. Probabilistic Systems Analysis

EE 376A. Information Theory

ENGR 62. Introduction to Optimization (Same as MS&E 111)

ENGR 155C. Introduction to Probability and Statistics for Engineers (Same as CME 106)

ETHICSOC 20. Introduction to Moral Philosophy (Same as PHIL 20)

ETHICSOC 30. Introduction to Political Philosophy (Same as PHIL 30, PUBLPOL 103A)

HPS 60. Introduction to Philosophy of Science (Same as PHIL 60)

HUMBIO 21. Introduction to Brain and Behavior (Same as BIO 20)

HUMBIO 145. Birds to Words: Cognition, Communication, and Language (Same as PSYCH 137/239A)

HUMBIO 160. Human Behavioral Biology (Same as BIO 15/250)

LINGUIST 1. Introduction to Linguistics

LINGUIST 83N. Translation

LINGUIST 105/205A. Phonetics

LINGUIST 110. Introduction to Phonetics and Phonology

LINGUIST 120. Introduction to Syntax

LINGUIST 124A/224A. Introduction to Formal Universal Grammar

LINGUIST 130A. Introduction to Linguistic Meaning

LINGUIST 130B. Introduction to Lexical Semantics

LINGUIST 140/240. Language Acquisition I

LINGUIST 180/280. From Languages to Information (Same as CS 124)

LINGUIST 181/281. Grammar Engineering

LINGUIST 182/282. Computational Theories of Syntax

LINGUIST 188/288. Natural Language Understanding (Same as CS 224U)

LINGUIST 210A. Phonology

LINGUIST 210B. Advanced Phonology

LINGUIST 221A. Foundations of English Grammar

LINGUIST 221B. Studies in Universal Grammar

LINGUIST 222A. Foundations of Syntactic Theory I

LINGUIST 230A. Introduction to Semantics and Pragmatics

LINGUIST 230B. Semantics and Pragmatics

LINGUIST 232A. Lexical Semantics

LINGUIST 235. Semantic Fieldwork

LINGUIST 241. Language Acquisition II

LINGUIST 247. Seminar in Psycholinguistics (Same as PSYCH 227)

LINGUIST 278. Programming for Linguists

LINGUIST 284. Natural Language Processing (Same as CS 224N)

LINGUIST 285. Speech Recognition and Synthesis (Same as CS 224S)

LINGUIST 286. Information Retrieval and Web Search (Same as CS 276)

LINGUIST 289. Quantitative, Probabilistic, and Optimization-Based Explanation in Linguistics

MATH 113. Linear Algebra and Matrix Theory

MATH 151. Introduction to Probability Theory

MATH 162. Philosophy of Mathematics (Same as PHIL 162)

ME 115B. Product Design Methods

MS&E 120. Probabilistic Analysis

MS&E 121. Introduction to Stochastic Modeling

MS&E 201. Dynamic Systems

MS&E 430. Tools for Experience Design

MUSIC 151. Psychophysics and Cognitive Psychology for Musicians

MUSIC 128. Composition, Coding, and Performance with SLOrc (Same as CS 170)

MUSIC 220A. Fundamentals of Computer-Generated Sound

MUSIC 220B. Compositional Algorithms, Psychoacoustics, and Spatial Processing

MUSIC 250A. HCI Theory and Practice

MUSIC 251. Music, the Brain, and Human Behavior

MUSIC 253. Musical Information: An Introduction

MUSIC 254. Applications of Musical Information: Query, Analysis, and Style Simulation

NBIO 206. The Nervous System

NBIO 218. Neural Basis of Behavior

PHIL 9N. Philosophical Classics of the 20th Century

PHIL 10. God, Self, and World: An Introduction to Philosophy

PHIL 14N. Belief

PHIL 80. Mind, Matter, and Meaning

PHIL 102. Modern Philosophy, Descartes to Kant

PHIL 143/243. Quine

PHIL 150. Basic Concepts in Mathematical Logic

PHIL 151. First-Order Logic

PHIL 152. Computability and Logic

PHIL 154. Modal Logic

PHIL 155. General Interest Topics in Mathematical Logic

PHIL 157. Topics in Philosophy of Logic

PHIL 164. Central Topics in the Philosophy of Science: Theory and Evidence

PHIL 166. Probability: Ten Great Ideas About Chance

PHIL 167B. Philosophy, Biology, and Behavior

PHIL 180A/280A. Realism, Anti-Realism, Irrealism, Quasi-Realism

PHIL 181. Philosophy of Language

PHIL 184. Theory of Knowledge

PHIL 184B. Philosophy of the Body

PHIL 184P. Probability and Epistemology

PHIL 186. Philosophy of Mind

PHIL 187. Philosophy of Action

PHIL 188. Personal Identity

PHIL 189/289. Examples of Free Will

PHIL 194C. Time and Free Will

PHIL 194P. Naming and Necessity

PHIL 194R. Epistemic Paradoxes

PHIL 279. Collectivities

PHIL 350A. Model Theory

PHIL 351A. Recursion Theory

PHIL 354. Topics in Logic

PHIL 366. Evolution and Communication

PHIL 382A. Pragmatics and Reference

PHIL 387. Practical Rationality

PHIL 387C. Consistency and Coherence

PSYCH 1. Introduction to Psychology

PSYCH 7Q. Language Understanding by Children and Adults

PSYCH 23N. Aping: Imitation, Control, and the Development of the Human Mind

PSYCH 30. Introduction to Perception

PSYCH 45. Introduction to Learning and Memory

PSYCH 50. Introduction to Cognitive Neuroscience

PSYCH 55. Introduction to Cognition and the Brain

PSYCH 70. Introduction to Social Psychology

PSYCH 75. Introduction to Cultural Psychology

PSYCH 104. Uniquely Human

PSYCH 122S. Introduction to Cognitive and Comparative Neuroscience

PSYCH 131/262. Language and Thought

PSYCH 133. Human Cognitive Abilities

PSYCH 134. Seminar on Language and Deception

PSYCH 141. Cognitive Development

PSYCH 143. Developmental Anomalies

PSYCH 154. Judgement and Decision-Making

PSYCH 159. Psychology of Attitude Change and Social Influence

PSYCH 202. Cognitive Neuroscience

PSYCH 204A. Human Neuroimaging Methods

PSYCH 209/209A. The Neural Basis of Cognition: A Parallel Distributed Processing Approach

PSYCH 209B. Applications of Parallel Distributed Processing Models to Cognition and Cognitive Neuroscience

PSYCH 226. Models and Mechanisms of Memory

PSYCH 227. Seminar in Psycholinguistics (Same as LINGUIST 247)

PSYCH 232. Brain and Decision Making

PSYCH 246. Cognitive and Neuroscience Friday Seminar

PSYCH 250. High-level Vision

PSYCH 251. Affective Neuroscience

PSYCH 252. Statistical Methods for Behavioral and Social Sciences

PSYCH 253. Statistical Theory, Models, and Methodology

PSYCH 272. Special Topics in Psycholinguistics

SOC 126/226. Introduction to Social Networks

STATS 110. Statistical Methods in Engineering and the Physical Sciences

STATS 116. Theory of Probability

STATS 191. Introduction to Applied Statistics

STATS 200. Introduction to Statistical Inference

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