Techniques of Artificial Intelligence

Time: 

From February 12th, 2018 on Mondays between 10h - 12h at the ULB Solbosch campus in Room AY2-112 (https://www.ulb.ac.be/campus/solbosch/plan-en.html)

External lecturer: 
External assistant: 
Objectives: 
  • Introduction: Philosophy of Artificial Intelligence
    • What is AI?
      • Approaches, Foundations, History
      • Applications and the future
  • Rational Agents
    • Computational entities that exhibit intelligent behaviour
  • Knowledge Representation and Problem Solving
    • Formal Logic as a Representation Language
    • Representing Problems and Solving Them
    • Building Programs that can Solve Problems
    • Automated Reasoning
    • Reasoning with Uncertainty
  • Machine Learning
Prerequisites: 

Basics of statistics and programming.

Description: 
  • Introduction to AI
  • Intelligent Agents
  • Knowledge Representation and Reasoning
  • Proof by Resolution
  • Problem Solving and Search
  • Local search and games
  • Stochastic methods in AI
  • Learning of concepts (version spaces and decision trees)
  • Datamining
  • Reinforcement Learning
  • Bayesian Learning
  • Neural Networks
  • Evaluation of Hypotheses
  • Computational learning theory
  • Heuristic Optimisation

 

Examination: 

VUB/ULB students: Exam + Project.

The exam is open book, however no laptops or mobile phones are allowed.
Schedule: 

Topics 

  • 12/02 Introduction to AI
  • 19/02 Intelligent Agents

Schedule

You can find the VUB schedule here.

Excercises 

* Mondays from 1:30pm to 4:30pm in room D3.07  in weeks 23, 25, 27-28, 32-35.

Material: 

Handbook Tom Mitchell ( slides)

Handbook Artificial Intelligence: A Modern Approach, by Russel and Norvig (http://aima.cs.berkeley.edu/)

Handbook The essence of Artificial Intelligence, by Alison Cawsey (http://www.macs.hw.ac.uk/~alison/essence.html) (Chapters 1-4)

Tutorial for Data Clustering

Applets

Example Exams

June 2012

June 2011