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T-622-ARTI, Introduction to Artificial Intelligence, Spring 2016

Description

Artificial Intelligence (AI) is devoted to the computational study of intelligent behaviour, including areas such as problem solving, knowledge representation, reasoning, planning and scheduling, machine learning, perception and communication. This course gives an overview of the aforementioned AI subfields from a computer science perspective and introduces fundamental solution techniques for addressing them. An important part of the course is an independent final project where the students develop AI software in an area of their choice.

Help

For questions and discussions about the lectures, homework, projects and AI in general go to the Piazza page of the course.

Goals

On the completion of the course the students should:

  • have a good overview of the field of artificial intelligence (AI) and a thorough understanding of the fundamental solution methods used to attack a wide variety of AI-related problems.
  • have gained experience building a small special-purpose AI system.

Book

The textbook for this class is: “Artificial Intelligence: A Modern Approach” by Stuart Russell and Peter Norvig. This book has a good web site full of useful AI resources.

Coursework Overview

Homework Assignments/Labs (20%)

You hand in the (almost) weekly homework assignments and finish the labs. The assignments will mainly consist of small exercises in which you have to apply what you should have learned in the lecture. The questions should give you an indication of the questions that may be asked in the final exam. The labs are more practical applications of the material, often in the form of small programming tasks.

Programming assignments (2 x 10%)

You complete two programming assignments. This can be done as a group project (up to 4 people, ideally 2-3). Make sure you clearly indicate who is part of the group and that every group member clearly understands the solution.

The first programming assignment is to use search to find a good solution for a vacuum cleaning robot.

The second programming assignment is to program a breakthrough agent.

Project (20%)

You can choose a topic for the programming project (discuss topics and find a group on the Piazza page. Like the programming assignments, this can be done as a group project (up to 4 people). You have to hand in a 1-2 page description of the project goal and some ideas on how to achieve it approx. in week 7 (5% of the final grade) and a report in the last week (15% of the final grade).

Exam (40%)

There will be a final exam (3h) with questions similar to the ones in the assignments.

Grading

Part of CourseTotal Weight
Assignments, Labs 20%
2 Programming Assignments (2*10%) 20%
Project 20%
Final Written Exam 40%
Total 100%

Course Schedule (subject to change)

WeekDateChaptersTopic
1Jan 12 1Introduction, History
Jan 13 LabLab 1 - Agents
Jan 14 2Intelligent Agents, Search Problems
2Jan 19 3Search Problems, Blind Search
Jan 20 LabLab 2 - Hashing States
Jan 21 3Blind Search, Heuristic Search
3Jan 26 3Heuristic Search
Jan 27 LabProgramming Assignment 1 - Search (description on MySchool)
Jan 28 3Heuristic Search
4Feb 02 5Heuristic Search, Adversarial Search (Minimax, Alpha-Beta)
Feb 03 LabProgramming Assignment 1 - Search (description on MySchool)
Feb 04 6Adversarial Search (Algorithms), CSPs
5Feb 09 7CSPs
Feb 10 LabLab 3 - CSPs
Feb 11 7CSPs, Propositional Logic
6Feb 16 7,8,9Logical Agents
Feb 17 LabProgramming Assignment 2 - Breakthrough
Feb 18 8,9First Order Logic
7Feb 23 8,9First Order Logic
Feb 24 LabLab 4 - Propositional Logic
Feb 25 10Planning
8Mar 01 10Planning
Mar 02 LabProgramming Assignment 2 - Competition
Mar 03 13, 14Uncertainty, Bayesian Networks
9Mar 08 18-21Bayesian Networks, Machine Learning
Mar 09 LabLab 5 - Bayesian Networks
Mar 10 18-21Machine Learning
10Mar 15 18-21Learning Decision Trees
Mar 16 LabLab 6 - Learning Decision Trees
Mar 17 25Robotics
11Mar 22 15Probabilistic Reasoning over Time
Easter Break
12Mar 30 LabLab 7 - Particle Filtering
Mar 31 Wrap-Up
13Apr 05 Project Presentations
Apr 06 LabProject Presentations
Apr 07 Project Presentations
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