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S-114.220 / AS-84.J Research Seminar on Computational Science

The first topic of the course in spring 2005 is

Neurorobotics (3 cr) L V

D.Sc. Harri Valpola (LCE), Prof. Arto Visala (ATL)
The course is multidisciplinary and combines both theory and practice. The material consists of neuroscience, machine learning and robotics articles and the information will be applied in implementations with robots. The course requires active participation and teamwork.
You should be familiar with at least one of the following fields: The idea is that everybody contributes what they can given their background and skills.
Place and time
Lecture hall AS2 (TUAS House, Otaniementie 17) on Tuesdays at 14-16. The first lecture will be on the 25th of January.
The course is given jointly by LCE and ATL and therefore has two codes: S-114.220 and AS-84.J. You can choose the one which is convenient for you. During the first lecture, we will collect some information about the participants. Please contact Harri.Valpola [at] if you would like to participate but cannot attend the first lecture.


The main topic of the course is predictive motor control in vertebrates. The goal is to learn the neuroscience, machine learning and robotics aspects of this. Motivation for this type of course is that on one hand, robotics and machine learning can learn a lot from motor control and learning in animals. Roboticists can at the moment only dream of the skillful, adaptive movements of animals. On the other hand, robotics and machine learning gives a valuable system-level view to neuroscience. Traditionally neuroscience has been dominated by analysis and experimentation but the danger is that one becomes overwhelmed by details and the big picture remains obscure.

Apart from predictive motor control, some related topics (such as saccadic eye-movement control, visuo-motor control and task-adapted sensory processing) will be covered on a theoretical level but not in robotic implementation.

Understanding the articles covered during the course will require knowledge and skills in many different disciplines (neuroscience, robotics, machine learning, programming) but the students are not required to have prior knowledge on all of these fields. Rather, the participants should be prepared to work in multidisciplinary teams and share their knowledge with other team members with different backgrounds.


The teams were selected and projects outlined
There is now a page for articles and other material
Jari Saarinen sketched the communication architechture
A new sketch of the communication protocol
Communication protocol and data collected with the robot on J2B2-page
Cortex group (team 3) has published a Homepage
We decided to extend the course because the implementations of the different parts of the control architecture are not at the stage where they could be integrated.


Date Speaker Topic
25.1 Harri Valpola Overview of the course and introduction to vertebrate motor system
25.1. Mika Vainio Introduction to robotics
1.2. Selection of teams and outline of projects
1.2. Jari Saarinen (Team 1) Basics of feedback control
8.2. Team 2 Feedback control and predictions
15.2. Team 3 Representations and sensory processing
22.2. Team 4 Reinforcement learning and action selection
1.3. Discussion about the communication architecture, first experiments and tasks
8.3. Discussion about the communication protocol and details of implementation
15.3. More discussion about implementation
22.3. Discussion about uses of predictor: forward and inverse models
29.3. Easter holiday
5.4.-3.5. Discussion about the implementations. Each group reports their progress. Gradually the work is integrated together.
10.5. Final meeting and demonstration of the integrated control architecture

D.Sc. Harri Valpola
Harri.Valpola at

Maintained by Harri Valpola
Last updated 28.04.2005