Leon Reznik: Foundations of Intelligent Systems

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Catalogue Description

An introduction to the theories and algorithms used to create intelligent systems. Topics include search algorithms (e.g. A*, iterative deepening), logic, planning, knowledge representation, machine learning, and applications from areas such as computer vision, robotics, natural language processing, and expert systems. Programming assignments and oral/written summaries of research papers are required. (CSCI 603, CSCI 605, and CSCI 661, with B or better in all courses) or equivalent or permission of instructor (students who complete CSCI 331 may not take CSCI 630 for credit)

Course Outcomes

Students will be able to describe the attributes of various search techniques and the situations to which they are well-suited. (supports Program Outcome 1) Evaluation: Written Assignments, Exams
Students will be able to describe and apply various techniques for logic programming and machine learning. (supports Program Outcome 2) Evaluation: Written Assignments, Exams
Students will be able to implement standard AI algorithms. (supports Program Outcome 2) Evaluation: Programming Projects
Students will be able to discuss the history and implications of artificial intelligence research. (supports Program Outcome 5) Evaluation: Written Assignments, Exams
Students will be able to summarize research papers orally and in writing. (supports Program Outcomes 3 and 4) Evaluation: Oral presentation and research papers summaries

Course Policies

This class may be taught in a blended mode; in this case the class meeting time will be reduced but the students will have to do more work independently and online, please, see Welcome to my class letter and mycourses for further information