I expect that you have a personal copy of the textbook, and quizzes and exams are written accordingly. Spring 2019 (12 units) Class times: T/Th 4:30 pm - 5:50 pm (Eastern time), Hamburg Hall 1204 and on-line . You must demonstrate your mastery by (1) accurate performance on frequent quizzes and exams, and (2) successful implementation of an AI coding project. Artificial Intelligence: A Modern Approach. Reading: Chapters 1, 2, and 3. I honor all requests made by the UCI Disability Services Center. In particular, you will learn about the methods and tools that will allow you to build complete systems that can interact intelligently with their environment by learning and reasoning about the world. We will use a course Piazza page for questions & discussion. Course code: TIN175/DIT411. In computer science, artificial intelligence, sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans. Your educational moments are precious, and your education now will be the single most important factor in your future career success or failure. There will be one final project at the end of the semester. Russell and Norvig. Reinforcement Learning: An Introduction. Except for properly referenced material, you or your team must write all of your own project report by yourself. Artificial Intelligence in the Movies 2. Essentials of Artificial Intelligence. The ICS Student Affairs Office will be involved at every step of the process. Please work harder and study longer. The course objectives are to learn the fundamental theories, algorithms and concepts in Artificial Intelligence. Week 1 Representation, Problem Spaces, Weak Search. A comprehensive reference for all the AI topics that we will cover. This is an individual or pair project, i.e., you must do it entirely by yourself or form a team of two people. If for any reason you miss a class, it is your responsibility to review all the material covered in the class and to complete the corresponding reading and programming assignments. Revised January 19 th, 2020. Introduction to Artificial Intelligence V22.0480.001 Monday and Wednesday, 2:00-3:15 Room 101, Warren Weaver Hall Professor Ernest Davis Reaching Me. Academic dishonesty is unacceptable and will not be tolerated at the University of California, Irvine. Students must make sure their Blackboard login is working at the beginning of the course. Course Learning OutcomesUpon successful completion of this course, the students will be able to: There will be quizzes assigned based on the material covered during the lecture as well as the assigned readings. Discussion Section is required and roll will be taken, because it is part of our educational mission to train our TAs to become future professors. I deliberately treat you as adults who are responsible for your own educational decisions, and so Lecture is optional. Homework is assigned but ungraded. Please come to lectures and discussion sections prepared with questions about any material that is not clear. Week 2 Representation, Problem Spaces, Heuristic Search, A*, Branch and Bound. births/deaths in the family (I require a copy of the birth/death certificate), jury duty or other court proceedings (I require a copy of your jury service papers or other official court documents), or. Please do not jeopardize your precious educational experience with the false economy of trying to save a few dollars by not having a personal copy of the textbook. Please ask questions about any class material that is not absolutely crystal clear. Late labs will not be accepted and labs will be graded individually, even if you worked in a team. ; but you are forbidden to copy: (1) source code from any source, or (2) text from any source unless properly cited and set off as a quote. Homework will be assigned, but is not graded. Artificial Intelligence Syllabus for Class 7 1. You will be expected to learn and master a large body of technical material in a very short period of time. Please purchase or rent your own personal textbook. Credits: 7.5 (7,5 hp) Course edition: Spring 2019 (VT19) Course provider: Department of Computer Science and Engineering, Chalmers University of Technology and University of Gothenburg. Probabilistic Graphical Models. ; or search the web for other sites related to the textbook. Quizzes will cover mostly material presented since the last quiz, and also may include questions that many students missed on the previous quiz. The policies in these documents will be adhered to scrupulously. Please work and understand all past quizzes and exams; they are important guides about the performance that will be expected from you now. You must write the “smarts.” This is a solo or pair project and you must do all of it all by yourself or with a single team-mate.