CS 4100/5100: Foundations of Artificial Intelligence

Spring 2014
Tuesdays and Fridays 9:50-11:25 (Lecture)

Lecture Notes
Week's Topics


    Magy Seif El-Nasr
    Office 136
    Meserve Hall
    Office Hours: by appointment
    email: magy at neu dot edu


    Truong Huy Nguyen Dinh
    Post Doctoral Fellow
    Playable Innovative Technology Lab
    Email: truonghuy at gmail dot com


    Prashanth Ramanna
    Masters Student
    Email: ramanna.p at husky dot neu dot edu

Canvas Course Link
Course Description:
Introduces the fundamental problems, theories, and algorithms of the artificial intelligence field. Includes heuristic search; knowledge representation using predicate calculus; automated deduction and its applications; planning; and machine learning. Additional topics include game playing; uncertain reasoning and expert systems; natural language processing; logic for common-sense reasoning; ontologies; and multiagent systems.
Pre-requisites: CS 2800 and CS 3500

Grading rubrics are established for each assignment. For assignments, demonstration of code execution will merit understanding of the concepts (80%). 20% of the assignment will be based on code review done by instructor. For the project assignment, different criteria are used. In particular, the criteria will include: (a) demonstration of presentation skills through presentation of the project ideas and final project, (b) creativity in selection and development of the game pitch, (c) demonstration of writing and communication abilities, and (d) demonstration of ability to work in group and manage complexity of the project.
  • Individual Assign0 (5%)
  • Individual Assignments (20%) – 2 assignments (Assign1, Assign2)
  • Pair-Programming Assignments (10%) – In groups of 2 (Assign3)
  • Quizzes (20%)
  • Project (45%) – group of 4-5
    • Iteration 1: 10% (written and code)
    • Iteration 2: 10% (written and code)
    • Iteration 3: 10% (written and code)
    • Final: 10% (written and code)
    • Pitch: 0% advancement to planning (presentation)
    • Project Plan: 0% advancement to iteration 1 (online document)
    • Project Management (5%) – keep updating the schedule and reporting

Course Syllabus (Last updated Dec 26, 2013).