IN4015 Neural networks

The course covers techniques from Artificial Intelligence and Machine Learning to create adaptive systems that learn to act in complex, dynamic environments through interaction with that environment.

The emphasis will be on techniques that take their inspiration from biology. Topics include: neural networks, evolutionary computation, learning classifier systems, swarm intelligence, artificial immune systems, subsumption architecture and embodiment.

The course is set up as a seminar, i.e. during the lectures we will discuss papers. As usual the lectures are split up in two �hours� of 45 minutes. In each hour we will discuss one (sub)topic. The topic will first be presented by 1 or 2 people from the group (about 20 min.) after which we will discuss the topic with the whole group.

The second part of the course is a practical assignment. In groups of max. 3 people you will experiment with one or more of the techniques discussed during the lectures by implementing them in a (simulated) robot, e.g. to make a (group of) robots learn to navigate, to recognize or move certain objects or to communicate with each other. You can apply the technique you discussed during the lectures, but you may also use other techniques.

Teachers

Last modified: 2023-11-03