Evolutionary robotics
Summary
The course covers theories, methods, and technologies for designing robots and artificial systems inspired by evolution, development, and learning. It shows how robotic models help understand biological systems and includes programming exercises using MuJoCo and gym.
Content
- Natural and Artificial Evolution
- Principles of Evolutionary Computation
- Algorithms: Genetic Algorithms and Evolutionary Strategies
- Algorithms: Multi-objective optimization (various algorithms, including NSGA-II)
- Intorduction to neural netwok architectures and learning methods, including reinforcement learning
- Evolution of Artificial Neural Networks and comparison to Reinforcement Leanring
- Evolution of Neurocontrollers for mobile robots
- Morphological Growth and Evolution
- Evolution of Collective Systems: Competitive and Cooperative Evolution
- Evolution of bio-hybrid robots
Learning Prerequisites
Important concepts to start the course
Python
Learning Outcomes
By the end of the course, the student must be able to:
- Apply tate-of-the-art software tools for robot simulation
- Translate acquired theoretical knowledge in practical implementations during exercise sessions
Teaching methods
Lectures, software exercises, and final report on an evolutionary robotics experiment in simulation.
Expected student activities
Attending lectures, asking critical questions, taking all exercises and completing assignments for the following week, forming groups and performing collaboratively project with evolutionary robotics software, writing report on project results.
Assessment methods
Mini-project report in powerpoint + presentation + written exam
Supervision
| Office hours | No |
| Assistants | Yes |
| Forum | Yes |
Resources
Bibliography
Floreano, D. & Mattiussi, C. (2008) Bioinspired Artificial Intelligence. MIT Press (selected chapters)
Ressources en bibliothèque
Moodle Link
Dans les plans d'études
- Semestre: Printemps
- Forme de l'examen: Ecrit (session d'été)
- Matière examinée: Evolutionary robotics
- Cours: 2 Heure(s) hebdo x 14 semaines
- Projet: 2 Heure(s) hebdo x 14 semaines
- Type: optionnel
- Semestre: Printemps
- Forme de l'examen: Ecrit (session d'été)
- Matière examinée: Evolutionary robotics
- Cours: 2 Heure(s) hebdo x 14 semaines
- Projet: 2 Heure(s) hebdo x 14 semaines
- Type: optionnel
- Semestre: Printemps
- Forme de l'examen: Ecrit (session d'été)
- Matière examinée: Evolutionary robotics
- Cours: 2 Heure(s) hebdo x 14 semaines
- Projet: 2 Heure(s) hebdo x 14 semaines
- Type: optionnel
- Semestre: Printemps
- Forme de l'examen: Ecrit (session d'été)
- Matière examinée: Evolutionary robotics
- Cours: 2 Heure(s) hebdo x 14 semaines
- Projet: 2 Heure(s) hebdo x 14 semaines
- Type: optionnel
- Forme de l'examen: Ecrit (session d'été)
- Matière examinée: Evolutionary robotics
- Cours: 2 Heure(s) hebdo x 14 semaines
- Projet: 2 Heure(s) hebdo x 14 semaines
- Type: optionnel