MIT OpenCourseWare

Browse materialsMIT 6.871 · Spring 2005

Knowledge-Based Applications Systems

Subjects: Artificial Intelligence · Engineering · Technology

Art: Palmer, Edward, 1803-1872, Figures 113-123. Plate Electrical Machines, 1840 · Public domain

Instructor: Prof. Randall Davis
Term: Spring 2005
Level: Graduate
What's inside: 1 lecture note · 1 reading · 66 other files · 4 web pages
Materials open: MIT OCW

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About this course

Source: MIT OpenCourseWare 6.871 Knowledge-Based Applications Systems, Spring 2005, Prof. Randall Davis — original course page on ocw.mit.edu ↗. License: CC BY-NC-SA 4.0. Study order: MIT's own listing order, section by section. Taken from MIT's published course files, downloaded from ocw.mit.edu on September 23, 2026. How RedLectern is built.

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Prerequisites are not listed here. Check MIT's own syllabus for this course.

How this course was organized

What's here, and what isn't

A lecture sequence of 26 items is confirmed. Assignment and exam materials exist too, but MIT's own order for them could not be verified, so they're shown as materials below rather than a sequence.

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Materials by section

Grouped by section, as MIT organized them. Not sequenced or ordered.

Lecture Notes

15 files

Assignments

18 files

Projects

27 files

Other materials from this course

MIT OpenCourseWare, Prof. Randall Davis, 6.871 Knowledge-Based Applications Systems, Spring 2005.

License: CC BY-NC-SA 4.0 · Edition: Spring 2005 · Open the original course on OCW ↗

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Knowledge-Based Applications Systems

Before you start

What's here, and what isn't

Not included here

Materials by section

Lecture Notes

Assignments

Projects

Other materials from this course

Lecture 1: Course Organization; Spirit of the Undertaking

Lecture 2: Tell it What to Know; Search

Lecture 3: Origins of KBS: MACSYMA and DENDRAL

Lecture 4: Application Analysis Case Study: Case Introduction

Lecture 5: Application Analysis Case Study: Class Discussion

Lecture 6: Rule-Based Systems

Lecture 7: Semantic Nets

Lecture 8: Logic

Lecture 9: Frame-Based Systems

Lecture 10: Uncertain Reasoning, Models of Rationality

Lecture 11: Blackboards

Lecture 12: Pragmatic Issues in Knowledge Acquisition

Lecture 13: Summary of Knowledge Representation

Lecture 14: Causal Reasoning

Lecture 15: Model-Based Reasoning

Lecture 16: Case-Based Reasoning

Lecture 17: Reasoning with Constraints

Lecture 18: Reasoning about Physical Systems

Lecture 19: Human Intelligence Project

Lecture 20: Common Sense

Lecture 21: Learning

Lecture 22: Ontologies and Data Mining

Lecture 23: Project Presentations and Discussion

Lecture 24: Project Presentations and Discussion (cont.)

Lecture 25: Project Presentations and Discussion (cont.)

Lecture 26: Project Presentations and Discussion (cont.)