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Artificial Intelligence, Fall 2006

 
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Type: Course Related Materials
Grade Level: Post-secondary
Author: Winston, Patrick Henry
Subject: Science and Technology
Institution Name: M.I.T.
Collection Name: MIT OpenCourseWare

Abstract: Introduces representations, techniques, and architectures used to build applied systems and to account for intelligence from a computational point of view. Applications of rule chaining, heuristic search, constraint propagation, constrained search, inheritance, and other problem-solving paradigms. Applications of identification trees, neural nets, genetic algorithms, and other learning paradigms. Speculations on the contributions of human vision and language systems to human intelligence. Enrollment may be limited. 6.034 is the header course for the department's "Artificial Intelligence and Applications" concentration. This course introduces students to the basic knowledge representation, problem solving, and learning methods of artificial intelligence. Upon completion of 6.034, students should be able to: develop intelligent systems by assembling solutions to concrete computational problems, understand the role of knowledge representation, problem solving, and learning in intelligent-system engineering, and appreciate the role of problem solving, vision, and language in understanding human intelligence from a computational perspective.

Details

Course Type: Full Course
Material Types: Syllabi, Homework and Assignments, Assessments
Media Formats: Text/HTML, Downloadable docs
Language: English

Additional Information

Geographic Regional Relevance: All

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