Topic outline

  • Evolutionary Robotics

    The course describes theories, methods, and technologies for the automatic design of robot brains and morphologies using evolutionary and neuronal computation. It also shows how such methods can be used to understand biological systems. In addition to ex-cathedra lessons, students will carry out lab exercises and participate in team projects on the co-evolution of robotic brains and bodies, including the 3D printing of robotic parts and assembly of the evolved robots.

    Book coverTextbook: Floreano, D. and Mattiussi, C. (2008) Bio-inspired Artificial Intelligence. Cambridge, MA: MIT Press

    Credits: 3

    Every Wednesday, 13.00-16.00

    Rooms: (Lectures: MED 0 1418 - Labs:  BC 07)

    Final written exam: Monday 19 June 2017, 08:15-10:00, INJ 218

    Written exam consists in 20 Multiple-Choice Questions in 90 minutes.

    50% of the grade is given by final written exam, 50% by a written report and presentation of the project.


  • Introduction to Artificial Evolution

    22 February 2017

    DNA dice


    Lecture: Introduction to the course

    Lecture: Foundations of Evolutionary Computation

    Lecturer: Dario Floreano 





  • Artificial Neural Networks

    Neural network1 March 2017

     

    Lecture: Foundations of Artificial Neural Networks

    Lecturer: Dario Floreano


  • Evolutionary Algorithms Lab

    8 March 2017

    Artificial selection


    Lab: Evolutionary Algorithms

    Teaching Assistants: Davide Zappetti, Anand Bhaskaran






  • Evolutionary Robotics

    15 March 2017


    evolving neural network

    Lecture: Deep Learning

    Lecture: Introduction to Evolutionary Robotics

    Lecturer: Dario Floreano





  • Developmental Systems

    development

    22 March 2017

    Lecture: Developmental Systems
    Lecturer: Dario Floreano

    Lecture: Introduction to Robogen software

    Lecturer: Davide Zappetti

  • Evolutionary Robotics Lab

    29 March 2017


    Lab: Evolutionary Robotics

    Teaching Assistants: Davide Zappetti, Anand Bhaskaran


  • Robogen software & project planning

    5 April 2017


    Lab: RoboGen body-brain co-evolution

    Lab: Project Planning + group formation

    Teaching Assistants: Davide Zappetti, Anand Bhaskaran



  • Robogen Hardware

    12 April 2017

    Lecture: Introduction to robot 3D printing and assembly

    Lecturer: Przemek Kornatowski

    Lab: Robogen software (continued)
    Teaching Assistants: Davide Zappetti, Anand Bhaskaran


  • Statistics

    Statistics26 April 2017


    Lecture: A refresher of Statistics for Experiments

    Lecturer: Dario Floreano


    Lab: Informal Robogen project presentations to TAs

    Teaching Assistants: Davide Zappetti, Anand Bhaskaran




  • Co-evolutionary Robotics

    predator prey3 May 2017


    Lecture: Competitive and Cooperative Co-Evolution
    Lecturer: Dario Floreano

    Lab: Robogen session
    Teaching Assistants: Davide Zappetti, Anand Bhaskaran

     

  • Intermediate Robogen Presentations


    10 May 2017


    Teaching Assistants:  Davide Zappetti, Anand Bhaskaran, Przemek Kornatowski, Gregoire Heitz


  • Robogen Lab

    17 May 2017


    Feedback on course evaluation (10 minutes)

    Lecturer: Dario Floreano

    Robogen session: individual group coaching session

    Dario Floreano + teaching assistants (Davide Zappetti, Anand Bhaskaran, Przemek Kornatowski, Gregoire Heitz)


    • Robogen Lab

      24 May 2017


      Lab: Robogen project

      Teaching Assistants: Davide Zappetti, Anand Bhaskaran, Przemek Kornatowski, Gregoire Heitz


      • Final Robogen presentations

        31 May 2017

        - Students must hand in project presentations in powerpoint format 

        - Each student group will present the problem, method, and results obtained. Students will also present the robots and show how they work.

        - The presentation and contents of the report will be graded and contribute 50% to the final course grade.

        - [Report Submission Extension] Students must submit the reports in pdf format latest by 8 June at 23:59. You can submit by sending to davide.zappetti@epfl.ch