ITCS 6150/8150: Intelligent Systems
Please note that this syllabus is subject to change over the course of the semester. Updates will be made available on the course website.
Course mode
Possible mode be
Face-to-Face
Hybrid = Face-to-Face (F2F) + Online Asynchronous Instructional Method
Online Asynchronous
What is online asynchronous? - "Not being delivered in person or in real time. Asynchronous learning allows you to take online courses on your own schedule. Instructors provide materials, lectures, tests, and assignments that can be accessed at any time."
Course Topics (tentative) and Syllabus
What is AI? Problem Solving Agent, Problem Elements, Solving Problems by Searching, Search Strategies (BFS, Uniform cost search, DFS, Depth-limited search, Iterative deepening search), Theoretical comparison, Informed Search Methods (Best First Search and A*), Local Search Methods (Hill Climbing and its variants, Simulated Annealing, Genetic Algorithm), Constraint Satisfaction Problems (CSP) - solving map coloring and scheduling problems using forwarding checking, consideration of heuristics (MRV, DC, LCV, etc.), singleton propagation, AC3, Tree-structured CSPs, Local Search for CSPs (Min-conflicts heuristic and algorithm), Game Playing (minimax, alpha-beta pruning), Knowledge and Reasoning, Propositional Logic (in detail), First-Order-Logic (in detail), Uncertain Knowledge and Reasoning, Basics of Probability, Using Bayes' Rule for Reasoning, Constructing Bayesian Networks, Inference in Bayesian Networks, Making Decisions, Probabilistic Reasoning, Learning from observation, Supervised Machine Learning Algorithms.
Recommended Textbook(s)
[Artificial Intelligence: A Modern Approach, 4th Edition (3rd edition is good too), Stuart Russell, Peter Norvig, Pearson.[Required]
Introduction to machine learning, 3rd Edition, Alpaydin, Ethem, MIT Press.
Ebook - Atkins Library
Tentative Grading Scheme (Check Canvas)
Homework 20%
Activity 10%
Quiz 15%
Midterm 10%
Project 25%
Final exam 20%
Introduction and Prerequisites
Students must have solid background in programming languages, such as C/C++, Python, Java, or Prolog and must understand how computers work at a low level (as taught in the Computer Organizations and Systems courses), and must be able to apply basic mathematical concepts (as taught in the Discrete Math course). You will also be expected to master quite a bit of theoretical material and to apply knowledge to solve challenging problems.
Notes
This is an upper level computer science course. I assume you know how to program, how to debug. TA and Professor will help you but will not debug your code. You are expected to study materials, follow announcements, submit homework/project and take test on time. Assignments can be submitted to Canvas. Don't get behind in this class! And please feel free to contact TA and me, if you need help or further information.
Course Materials
Lectures and course materials, including presentations, tests, exams, outlines, and similar materials, are protected by copyright. You are free to take notes and make copies of course materials for your own educational use. However, you may not, nor must you allow others to reproduce or distribute lecture notes and course materials publicly without my express written consent.