Tutorial on Evolutionary Robotics
Organizers: Nicolas Bredeche (UPMC), Stephane Doncieux (UPMC), Jean-Baptiste Mouret (INRIA Lorraine)
- 7/2017: ACM GECCO 2017 - The Genetic and Evolutionary Computation Conference (Berlin, Germany)
- 9/2016: ICDL-EPIROB 2016 - International Conference Developmental Learning and Epigenetic Robotics (Cergy, France)
- Special focus for ICDL-EPIROB tutorial: In spite of the different starting points of Developmental Robotics and ER, many recent ideas introduced in the two fields are surprisingly similar. For example, open-ended evolution (e.g. Novelty Search) parallels intrinsic motivation in developmental robotics (Oudeyer and Kaplan, 2007), the behavior space in ER is similar to the goal space in Developmental Robotics (Rolf et al. 2010), and the relationships between simulation and reality is linked to self-modeling (Bongard et al., 2006). Inspired by these parallels, the main goal of this tutorial is to introduce recent ideas from ER that can be interesting for Developmental Robotics.
- 7/2015: ECAL 2015 - European Conference on Artificial Life (York, UK)
- 7/2015: GECCO 2015 - Genetic and Evolutionary Computation Conference (Madrid, Spain)
- 7/2014: IEEE ALIFE 2014 - Artificial Life Conference (New York, USA)
In the same way as evolution shapes animals, is it possible to use artificial evolution to automatically design robots? This attractive vision gave birth to Evolutionary Robotics (ER), an interdisciplinary field that incorporates ideas from Biology, Robotics and Artificial Intelligence. Within the last 20 years, Evolutionary Robotics explored many research avenues, from understanding Natural Evolution thanks to ER models, to co-designing robots' bodies and brains.
This tutorial will give an overview of the various questions addressed in ER, relying on examples from the literature. Past achievements and major contributions, as well as specific challenges in ER will be described. The tutorial will in particular focus on:
- what is evolutionary robotics?
- fitness function design and the influence of selection pressure;
- encodings of controllers and morphologies;
- evolution for physical robots and the reality gap;
- embodied evolution and collective robotics systems;
- open questions and future challenges.
Evolutionary robotics: what, why, and where to
Stephane Doncieux, Nicolas Bredeche, Jean-Baptiste Mouret and A.E. Eiben
Frontiers in Robotics and AI, 2015 (doi: 10.3389/frobt.2015.00004)
Click here to download the paper.