Evolutionary robotics
Summary
The course gives an introduction to evolutionary computation, its major algorithms, applications to optimization problems (including evolution of neural networks), and application to design and control of robots. It includes software exercises and project to evolve, build, and test a robot.
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
Programming skills (Phython, Java, C++)
Learning Outcomes
By the end of the course, the student must be able to:
- Apply new tools for software and hardware engineering
- Translate acquired theoretical knowledge in practical implementations during laboratory sessions
Teaching methods
Lectures, software exercises, and project involving evolution of morphology and neural control of robot, 3D printing of parts and assembly, test characterization of evolved robots.
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 physical robots, writing and presenting 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
In the programs
- Semester: Spring
- Exam form: Written (summer session)
- Subject examined: Evolutionary robotics
- Courses: 2 Hour(s) per week x 14 weeks
- Project: 1 Hour(s) per week x 14 weeks
- TP: 1 Hour(s) per week x 14 weeks
- Type: optional
- Semester: Spring
- Exam form: Written (summer session)
- Subject examined: Evolutionary robotics
- Courses: 2 Hour(s) per week x 14 weeks
- Project: 1 Hour(s) per week x 14 weeks
- TP: 1 Hour(s) per week x 14 weeks
- Type: optional
- Semester: Spring
- Exam form: Written (summer session)
- Subject examined: Evolutionary robotics
- Courses: 2 Hour(s) per week x 14 weeks
- Project: 1 Hour(s) per week x 14 weeks
- TP: 1 Hour(s) per week x 14 weeks
- Type: optional
- Semester: Spring
- Exam form: Written (summer session)
- Subject examined: Evolutionary robotics
- Courses: 2 Hour(s) per week x 14 weeks
- Project: 1 Hour(s) per week x 14 weeks
- TP: 1 Hour(s) per week x 14 weeks
- Type: optional
- Exam form: Written (summer session)
- Subject examined: Evolutionary robotics
- Courses: 2 Hour(s) per week x 14 weeks
- Project: 1 Hour(s) per week x 14 weeks
- Type: optional