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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%)

BSc:IntroductionToArtificialIntelligence old

Contents