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Syllabus for

Academic year
FFR125 - Autonomous agents  
 
Syllabus adopted 2010-02-25 by Head of Programme (or corresponding)
Owner: MPCAS
7,5 Credits
Grading: TH - Five, Four, Three, Not passed
Education cycle: Second-cycle
Major subject: Engineering Physics
Department: 16 - PHYSICS


Teaching language: English
Block schedule: X
Maximum participants: 40

Course module   Credit distribution   Examination dates
Sp1 Sp2 Sp3 Sp4 Summer course No Sp
0199 Examination 7,5 c Grading: TH   3,0 c 4,5 c   Contact examiner   23 Aug 2013 pm M

In programs

MPSYS SYSTEMS, CONTROL AND MECHATRONICS, MSC PROGR, Year 1 (elective)
MPCAS COMPLEX ADAPTIVE SYSTEMS, MSC PROGR, Year 1 (elective)

Examiner:

Professor  Mattias Wahde



Eligibility:

For single subject courses within Chalmers programmes the same eligibility requirements apply, as to the programme(s) that the course is part of.

Course specific prerequisites

Basic mathematical and programming skills are required. It is an advantage, but not absolutely necessary, to be familiar with Matlab. Some background concerning microcontrollers is advantageous, but not a requirement.

Aim

The course aims at giving the students an understanding of design principles for autonomous systems, both robots and software agens, and also gives students the opportunity to apply their knowledge in practice through the construction of a simple autonomous robot.

Learning outcomes (after completion of the course the student should be able to)

After successfully completing the course, the student will be able to:

Understand and describe basic properties of robotic hardware, including sensors, actuators and microcontrollers.
Describe the basics of animal behavior (ethology) and its connection to robotic behaviors.
Understand the basics of behavior-based robotics and evolutionary robotics.
Set up and use basic kinematic and dynamic equations for robot motion.
Define and set up computer simulations of wheeled autonomous robots (using a simulator provided by the lecturer).
Define and set up evolutionary simulations for the optimization of robotic control systems (using a simulator provided by the lecturer).
Understand and apply basic methods for behavior generation and behavior selection in autonomous robots.
Understand the basics of utility theory and its application in robotic behavior selection.
Understand and describe the basics of swarm intelligence and agent-based economics.
Construct and use a simple autonomous robot.

Content

The contents of the course are as follows

Theory of autonomous robots: Kinematics and dynamics
Behavior-based robotics
Evolutionary robotics
Utility theory, behavioral economics, theory of rational decision-making
Behavior selection in autonomous robots
Artificial life and swarm intelligence
Software agents, particularly agent-based economics
Learning in autonomous agents
Robot construction

Organisation

The course extends over two quarters. In the first part of the course, the theory is covered in 14 lectures. In the second part, a robot construction project is carried out (in groups of 5-6 students). In the final weeks of the course, the constructed robots are applied in a variety of simple tasks.

Literature

Lecture notes and handouts

Examination

The robot construction project is graded and corresponds to around 30% of the grade. 40% of the grade is determined based on the results of two home problems, and the remaining 30% are determined by the results on a written exam (at the end of the first half of the course).


Page manager Published: Thu 03 Nov 2022.