Project Artificial Intelligence

2019-2020

Course Objective

The course teaches students:
1) how to develop an intelligent agent (bot) based on standard
Intelligent Systems technology, and extensions thereof (Knowledge and
understanding) (Apply knowledge and understanding);
2) basic research and experimental analysis skills through the analysis
of how effectively the developed software performs in a controlled
scientific experiment. (Making judgements) (Communication) (Making
judgements) (Communication).

Course Content

In the course Project AI, a broad variety of techniques from the area of
Artificial Intelligence are applied, in particular those from the course
Intelligent Systems like adversarial search, knowledge representation
and machine learning.

The course focuses on the development and scientific analysis of methods
for rational agents that perform effectively in a card game (the
Austrian trick game Schnapsen). The outcome is a number of intelligent
game-bots, and a thorough evaluation of the impact of various AI
technology on their performance. The results of the experiment are
written in a scientific report. This experience provides students with
seminal skills that will be applied throughout the AI Bachelor study,
and through subsequent studies and career activities. This course
provides insights into how proper documentation of an experiment can
ensure that: - results are formulated objectively; - developed
scientific reports are well-specified and contain complete experiment
metrics.

Teaching Methods

There will be number of introductory lectures (refreshing relevant
knowledge and introducing the practical), as well as computer support
sessions (Labs). Work will be conducted in 4-person groups, but there
will be a personal evaluation component. The groups will be
self-directed, and will require to consult the course assistants during
practical sessions.

Method of Assessment

A final group report and an individual reflection on the process. There
will be a peer reviewing process for each paper by other students in the
course, which will help to determine a common mark for the group
project. There will also be a combination of self and peer reviewing to
individually balance grades within a group.

Entry Requirements

The knowledge taught in the course Intelligent Systems is required to
succeed in the course.

Literature

The literature required for this course will be distributed via Canvas.

Target Audience

BSc Artificial Intelligence (year 1)

Additional Information

As this course is a project-oriented course, the students are expected
to be working on this project individually for most of the time.
However, some of the lectures and practical sessions are mandatory to
ensure a good progress of each group.

General Information

Course Code X_401076
Credits 6 EC
Period P6
Course Level 200
Language of Tuition English
Faculty Faculty of Science
Course Coordinator C. Gerritsen
Examiner C. Gerritsen
Teaching Staff C. Gerritsen

Practical Information

You need to register for this course yourself

Last-minute registration is available for this course.

Teaching Methods Lecture, Practical
Target audiences

This course is also available as: