Neural computation is concerned with the discovery of new solutions to technical problems of information processing. These solutions are sought based on analogies with nervous systems and the behaviour of organisms.

This course focuses on three exemplary problems to illustrate this approach:
(a) Artificial action (autonomous robotics);
(b) Artificial perception (robot vision);
(c) Artificial cognition (simplest cognitive capabilities of autonomous robots such as decision making, scene representation, working memory, sequence generation, behavioral organization).

The main method is nonlinear dynamical systems applied to neural networks, leading to Dynamic Field Theory and neural dynamics.

Prof. Dr. Gregor Schöner Lecturer

(+49) 234-32-27965 gregor.schoener@ini.rub.de NB 3/31

Course type

Lectures

Credits

6 CP

Term

Summer Term 2015

Lecture

Takes place every week on Thursday from 14:15 to 16:00 in room NB 3/57.
First appointment is on 23.04.2015

Exercise

Takes place every week on Thursday from 16:15 to 17:00 in room NB 3/57.
First appointment is on 07.05.2015

Examination

Takes place on 14.08.2015 from 14:00 to 16:00 in room HZO 100.

Exercises

Usually, we upload an exercise sheet after each lecture. This sheet has to be handed in before the lecture of the following week (alternatively, you can hand it in via email to Oliver Lomp), which gives you a week to work on the solutions.

After collecting your solutions, we take a week to correct them and then discuss them in the exercise session following the lecture.

Exercises are corrected, and exercise sessions lead by Oliver Lomp.

Further reading

In case you are interested in additional material that goes beyond the scope of the course, have a look at our robotics school page. It contains more exercises, reading materials, slides and talks that have some overlap with the lecture.