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6.034 Notes: Section 1.1

Slide 1.1.2 These are the topics that we will cover during the semester. 6.034 is an introductory subject. Our goal is to give you a solid introduction to three key topics: search, knowledge representation and inference, and machine learning. We will introduce a variety of other different topics in AI, such as planning, robotics and natural language only in passing. Subsequent courses in AI cover those areas in more depth. | 6.034 Artificial Intelligence. Copyright 2004 by Massachusetts Institute of Technology. 6.034 Notes Section 1.1 Slide 1.1.1 This is a brief introduction to the content and organization of 6.034. Topics The course covers three major topics Search - Graph search - Constraint Satisfaction - Games Machine Learning - Nearest Neighbors - Decision Trees - Neural Networks - SVM Knowledge Representation Inference - Propositional First Order Logic - Rule-based systems - Natural Language tip Spring 02 2 Slide 1.1.2 These are the topics that we will cover during the semester. 6.034 is an introductory subject. Our goal is to give you a solid introduction to three key topics search knowledge representation and inference and machine learning. We will introduce a variety of other different topics in AI such as planning robotics and natural language only in passing. Subsequent courses in AI cover those areas in more depth. Slide 1.1.3 These are the formal and informal prerequisites for the subject. 6.001 is an essential prerequisite. In particular we expect you to read and understand substantial Scheme programs and to make small modifications to the code. Remember this is a subject in computer science. Programming is to CS as calculus is to physics and EE it is the essential language for making the ideas concrete. Also practice makes perfect and you should take every opportunity to practice programming. Scheme is the language that we can count on everyone having from 6.001 so we use it heavily. It is also highly suitable for many though not all of the topics covered in this subject. If you re going to study computer science you should take mastering programming languages in stride. We will assume that you know basic differential calculus of several variables and vector algebra such as covered in 18.02. You will not be able to understand machine learning without this basic mathematical background. Prerequisites 6.001 We will have regular assignments that expect you to be able to .