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1 - 10 of 18 results for: artificial intelligence

CS 54N: Great Ideas in Computer Science

Stanford Introductory Seminar. Preference to freshmen. Covers the intellectual tradition of computer science emphasizing ideas that reflect the most important milestones in the history of the discipline. No prior experience with programming is assumed. Topics include programming and problem solving; implementing computation in hardware; algorithmic efficiency; the theoretical limits of computation; cryptography and security; and the philosophy behind artificial intelligence.
Terms: Aut | Units: 3 | UG Reqs: GER:DB-EngrAppSci | Grading: Letter or Credit/No Credit
Instructors: Roberts, E. (PI)

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

Preference to freshmen. Can mental attitudes attributed to people and sometimes to animals, including knowledge, belief, desire, and intention, also be ascribed to machines? Can light sensors have a belief? Can a pool cleaning robot or tax-preparation software have an intention? If not, why not? If yes, what are the rules of such ascription, and do they vary between human beings and machines? Sources include philosophy, neuroscience, computer science, and artificial intelligence. Topics: logic, probability theory, and elements of computation. Students present a paper.
Terms: Aut | Units: 3 | UG Reqs: GER:DB-EngrAppSci | Grading: Letter or Credit/No Credit
Instructors: Shoham, Y. (PI)

CS 22: History and Philosophy of Artificial Intelligence (SYMSYS 22)

More than most emerging fields, the history of Artificial Intelligence has been characterized by passionate debates. Is it merely clever programming, or an expedition into the fundamental nature of intelligence? Will machines ever be conscious? Will robots assist or enslave us? Can self-driving cars be legally responsible for their actions? This course recounts the history of AI and explores the major controversies through a series of classroom discussions, each in preparation for a lively debate by prominent historical figures and cutting-edge researchers in the field. Open to all undergraduate and graduate students.
Terms: Aut | Units: 2 | Grading: Satisfactory/No Credit
Instructors: Kaplan, J. (PI)

CS 221: Artificial Intelligence: Principles and Techniques

Artificial intelligence (AI) has had a huge impact in many areas, including medical diagnosis, speech recognition, robotics, web search, advertising, and scheduling. This course focuses on the foundational concepts that drive these applications. In short, AI is the mathematics of making good decisions given incomplete information (hence the need for probability) and limited computation (hence the need for algorithms). Specific topics include search, constraint satisfaction, game playing, Markov decision processes, graphical models, machine learning, and logic. Prerequisites: CS 103 or CS 103B/X, CS 106B or CS 106X, CS 107, and CS 109 (algorithms, probability, and programming experience).
Terms: Aut | Units: 3-4 | Grading: Letter or Credit/No Credit
Instructors: Liang, P. (PI)

CS 227B: General Game Playing

A general game playing system accepts a formal description of a game to play it without human intervention or algorithms designed for specific games. Hands-on introduction to these systems and artificial intelligence techniques such as knowledge representation, reasoning, learning, and rational behavior. Students create GGP systems to compete with each other and in external competitions. Prerequisite: programming experience. Recommended: 103 or equivalent.
Terms: Spr | Units: 3 | Grading: Letter or Credit/No Credit

CS 222: Rational Agency and Intelligent Interaction (PHIL 358)

For advanced undergraduates, and M.S. and beginning Ph.D. students. Logic-based methods for knowledge representation, information change, and games in artificial intelligence and philosophy. Topics: knowledge, certainty, and belief; time and action; belief dynamics; preference and social choice; games; and desire and intention. Prerequisite: propositional and first-order logic.
Terms: not given this year | Units: 3 | Grading: Letter or Credit/No Credit

CS 294A: Research Project in Artificial Intelligence

Student teams under faculty supervision work on research and implementation of a large project in AI. State-of-the-art methods related to the problem domain. Prerequisites: AI course from 220 series, and consent of instructor.
Terms: not given this year | Units: 3 | Repeatable for credit | Grading: Letter or Credit/No Credit

CS 329: Topics in Artificial Intelligence

Advanced material is often taught for the first time as a topics course, perhaps by a faculty member visiting from another institution. May be repeated for credit.
Terms: offered occasionally | Units: 3 | Repeatable for credit | Grading: Letter or Credit/No Credit

ENGLISH 167: Contemporary Science Fictions and Technofutures

How do visions of the future shape the way we think about the present, and even the past? How does science fiction interrogate technological and scientific innovations as a versatile pop culture medium? We will consider the techniques the genre uses to creatively respond to ecological crisis, biologically engineered organisms, artificial intelligence, and information technology. Where does science fiction draw the line between humans and machines, technology and nature, and fact and fiction? This course will trace the genre¿s evolution, from its origins in Mary Shelley¿s Frankenstein, to more recent examples in contemporary literature, film, television and digital media.
Terms: Sum | Units: 3-5 | Grading: Letter or Credit/No Credit
Instructors: Felt, L. (PI)

LINGUIST 144: Introduction to Cognitive and Information Sciences (PHIL 190, PSYCH 35, SYMSYS 100)

The history, foundations, and accomplishments of the cognitive sciences, including presentations by leading Stanford researchers in artificial intelligence, linguistics, philosophy, and psychology. Overview of the issues addressed in the Symbolic Systems major.
Terms: Win | Units: 4 | UG Reqs: GER:DB-SocSci, WAY-FR | Grading: Letter or Credit/No Credit
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