Agents and Environments, Uninformed Search, Informed Search, A* Search and Heuristics, CSP I, CSP II, Adversarial Search I, Adversarial Search II, Markov Decision Processes I, Markov Decision Processes II, Reinforcement Learning I, Reinforcement Learning II, Probability, Bayes Nets I However, the scale may be shifted depending on overall studentĪll exams take place in our usual classroom, KUPF 107. The breakdown of the final course grade is as follows:Īt the end of the semester, letter grades will be assigned roughly according to Anyone who does not respect this policy will be asked to leave the classroom. Such activities make it hard, if not impossible, for the student to concentrate on the lecture and can also be very distracting to the lecturer and other students. Students should also refrain from emailing during class. Tiktoking, Tweeting, Tindering, Facebooking, Instagramming, Snapchatting, Whatsapping, YouTubing, and gaming are forbidden in the classroom. There is only one exception to this rule: a laptop or tablet may be used for, and only for, working on something related to the course material. Laptops may be used in the classroom only for work related to this course.Īs a general rule, students should silence and refrain from using all electronic devices (phones, ipods, tablets, microwave ovens, etc.) during all lectures and exam periods. Use of electronic devices in lecture for purposes unrelated to the course will not be tolerated. Violations of this policy will be dealt with in a manner consistent with university regulations, which range from a warning to expulsion from the university. In particular, cheating is unacceptable and will not be tolerated.
William demeo code#
Students must abide by the university's code of conduct.
It is impolite and disruptive to your classmates to leave, or even pack up your belongings, before the lecture is over. If you plan to leave before class is over, the correct procedure is to mention this to the professor before the start of class. Forging another student's signature constitutes a violation of the student code of conduct and will be referred to the dean.
If another student asks you to sign in for them, don't do it. Occasionally attendance will be recorded by passing around a sign-in sheet on which you will print and sign your own name. Each additional absence, and any absence not mentioned to the instructor, may result in the deduction of points from your final grade. Specifically, you are permitted (but strongly discouraged from taking) five absences in total, and you must email the instructor if/when you miss a class. A grade penalty will be exacted if you have an excessive number of absences (whether excused or unexcused). Students are expected to attend all classes. The Ghost in the Machine episode of This American Life, in which "people use machines to find people they lost.".Curiosity-driven Exploration by Self-supervised Prediction by Pathak, et al.Asynchronous Methods for Deep Reinforcement Learning by Mnih, et al.Distributed Representations of Words and Phrases and their Compositionality by Mikolov, et al.Reinforcement Learning: an introduction by Sutton and Barto.Curiosity Driven Deep Reinforcement Learning.Artificial Intelligence by Columbia University.These are not required but might be helpful. Students are expected to have access to the following textbook:Īrtificial Intelligence: A Modern Approach, 4th Edition (AIMA) Readings refer to the fourth edition of the required textbook (AIMA) unless otherwise indicated. See the syllabus for tentative lecture and homework schedule (subject to change). Prerequisite: CS 114 and ( MATH 226 or CS 241). Students are required to do programming assignments, complete a programming term project and review case studies." Some subset of the following programming languages will be used: LISP, Prolog, Python, and Scala. Topics include knowledge representation, parsing language, search, logic, adduction, uncertainty, and learning. Emphasizes both underlying theory and applications. (From the NJIT course catalog.) "An exploration of concepts, approaches and techniques of artificial intelligence. Students are expected to visit this page periodically. This page will be updated throughout the semester. You are now reading the main course web page and syllabus for CS 370. Send an email in advance to let the instructor know if/when you plan to attend office hours. The regularly scheduled office hours are subject to change.Ĭhanges will be announced during lecture. 10-11:20am Tue & Fri in KUPF 107Ĭourse Webpage. CS 370: Introduction to Artificial Intelligence (Section 004) NJIT Spring 2022
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