(Autonomous Agents) Intelligent agents/Autonomous robots

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  1. Recent updates
  2. Course description
  3. Schedule
  4. Problem sets
  5. Exams
  6. Links

  

1. Recent updates

This course is replaced by two courses starting spring 2017:  Intelligent agents and Autonomous robots. Intelligent agents home page: http://www.me.chalmers.se/~mwahde/courses/ia/2017/ia.html

 

2. Course description

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 outcome (after completion of this 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).

3. Schedule

Please have a look on the external course webpage for more information.

4. Problem sets

Please have a look on the external course webpage for more information.

5. Exams

Please have a look on the external course webpage for more information.

6. Links

External course webpage: http://www.me.chalmers.se/~mwahde/courses/aa/2014/aa.html

Mattias Wahde

Professor Mattias Wahde is researcher and teacher within the research group Adaptive Systems.The ultimate aim of his research is to generate autonomous robots capable of carrying out a variety of relevant tasks, particularly dangerous or tedious tasks which are presently carried out by people. His research is focused on generating robotic brains (control systems) rather than hardware (robots). In particular, he is developing a method (the utility function method) for behavioral selection. This method, as well as his research in general, is based on biologically inspired computation methods, particularly evolutionary algorithms (EAs).

Position: Professor