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Introduction to Artificial Intelligence

  • Course name: Introduction to Artificial Intelligence
  • Course number: XYZ
  • Knowledge area: Algorithms and Complexity

Administrative details

  • Faculty: Computer Science and Engineering
  • Year of instruction: 2nd year of BS
  • Semester of instruction: 2nd semester
  • No. of Credits: 4 ECTS
  • Total workload on average: 144 hours overall
  • Frontal lecture hours: 2 per week
  • Frontal tutorial hours: 2 per week
  • Lab hours: 2 per week
  • Individual lab hours: 0
  • Frequency: weekly throughout the semester
  • Grading mode: letters: A, B, C, D

Prerequisites

  • Discrete Math/Logic
  • English for Academic Purposes I

Course outline

Have you ever wondered about how computers decide on what your credit worthiness is, or how they can play chess as good as a world master, or how world class circuits can be built with a minimal number of crossed wires? Perhaps you have wanted to build a human like robot, or have wanted to explore the stars with automated probes. Artificial Intelligence is the field which examines such problems. The goal is to provide a diverse theoretical overview of historical and current thought in the realm of Artificial Intelligence, Computational Intelligence, Robotics and Machine Learning Techniques.

Expected learning outcomes

  • Understand and apply the PEAS model of problem definition
  • Understand and apply the Environment Model
  • Understand the role of AI within computer science in a variety of fields and applications
  • Gather an appreciation of the history of AI founders
  • Solve simple problems using random, guided, and directed, search methods and be able to compare their abilities to solve the problem using a statistical argument
  • Apply Evolutionary Algorithms, Neural Networks, Monte Carlo Tree Search to a number of problems

Expected acquired core competences

  • Automata
  • Compiler design
  • Formal methods
  • Formal models and semantics
  • Formal semantics
  • Proof techniques

Textbook

  • Russell & Norvig - Artificial Intelligence: A Modern Approach, 3rd Edition
  • Ashlock - Evolutionary Computation for Modeling and Optimization

Reference material

NA

Required computer resources

You will need a computer with a C/C++ and LISP compiler

Evaluation

  • Assignment 1 (20%)
  • Assignment 2 (20%)
  • Lab Participation (10%)
  • Midterm (25%)
  • Final (25%)