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Special Session on Evolutionary Robotics, IEEE CEC 2009

Evolutionary Robotics (ER) aims to apply evolutionary computation techniques, inspired by Darwin’s principle of selective reproduction of the fittest, to automatically design the control and/or hardware of both real and simulated autonomous robots.

Having an intrinsic interdisciplinary character, ER is being employed towards the development of many fields of research, among which we can highlight neuroscience, cognitive science, evolutionary biology and robotics. Hence the objective of this special session is to assemble a set of high-quality original contributions that reflect and advance the state-of-the-art in the area of Evolutionary Robotics, with an emphasis on the cross-fertilization between ER and the aforementioned research areas, ranging from theoretical analysis to real-life applications.

• Evolution of robots which display minimal cognitive behaviour, learning, memory, spatial cognition, adaptation or homeostasis.
• Evolution of neural controllers for robots, aimed at giving an insight to neuroscientists or advancing control structures.
• Evolution of communication, cooperation and competition, using robots as a research platform.
• Co-evolution and the evolution of collective behaviour.
• Evolution of morphology in close interaction with the environment, giving rise to self-reconfigurable, self-designing, self-healing and self-reproducing robots or humanoid and walking robots.
• Evolution of robot systems aimed at real-world applications as in aerial robotics, space exploration, industry, search and rescue, robot companions, entertainment and games.
• Evolution of controllers on board real robots or the real-time evolution of robot hardware.
• Novel or improved algorithms for the evolution or robot systems.
• The use of evolution for the artistic exploration of robot design.

Session Programme

• Active categorical perception in an evolved anthropomorphic robotic arm
  Elio Tuci, Gianluca Massera and Stefano Nolfi
• How Robot Morphology and Training Order Affect the Learning of Multiple Behaviors
  Joshua Auerbach and Josh C. Bongard
• A Multiple Hormone Approach to the Homeostatic Control of Conflicting Behaviours in an Autonomous Mobile Robot
  Renan Moioli, Patricia Vargas and Phil Husbands
• Reverse-engineering of Artificially Evolved Controllers for Swarms of Robots
  Sabine Hauert, Jean-Christophe Zufferey and Dario Floreano

• Memory-Enhanced Evolutionary Robotics: The Echo State Network Approach
  Cedric Hartland, Nicolas Bredeche and Michele Sebag
• A Hierarchical Conflict Resolution Method for Multi-Agent Path Planning
  Kuang-Yuan Chen, Peter A. Lindsay, Peter J. Robinson and Hussein A. Abbass
• A Distributed Pool Architecture for Genetic Algorithms
  Gautam Roy, Hyunyoung Lee, Jennifer Welch, Yuan Zhao, Vijitashwa Pandey and Deborah Thurston
• Multiobjective Quantum-inspired Evolutionary Algorithm for Fuzzy Path Planning of Mobile Robot
  Ye-Hoon Kim and Jong-Hwan Kim

• Evolving Coordinated Quadruped Gaits with the HyperNEAT Generative Encoding
  Jeff Clune, Benjamin Beckmann, Charles Ofria and Robert Pennock
• Co-evolving controller and sensing abilities in a simulated Mars Rover explorer
  Martin Peniak, Davide Marocco and Angelo Cangelosi
• Investigating the Effect of Pruning on the Diversity and Fitness of Robot Controllers based on MDL2e during Genetic Programming
  Marc Szymanski, Jan Fischer and Heinz Wörn
• Overcoming the bootstrap problem in evolutionary robotics using behavioral diversity
  Jean-Baptiste Mouret and Stephane Doncieux

Poster Sessions

• Evolutionary Robotics: The Next-Generation-Platform for On-line and On-board Artificial Evolution
  Serge Kernbach, Eugen Meister, Oliver Scholz, Raja Humza, Jens Liedke, Leonardo Ricotti, Jaouhar Jemai, Jiri Havlik and Wenguo Liu
• HyperNEAT Controlled Robots Learn How to Drive on Roads in Simulated Environment
  Jan Drchal, Jan Koutnik and Miroslav Snorek
• Multi-objective Evolution of Robot Neuro-Controllers
  Amiram moshaiov and Ariela Ashram - Wittenberg
• Open-ended On-board Evolutionary Robotics for Robot Swarms
  Baele Guy, Bredeche Nicolas, Haasdijk Evert, Maere Steven, Michiels Nico, Van de Peer Yves, Schmickl Thomas, Schwarzer Christopher and Ronald Thenius

• Learning Area Coverage for a Self-Sufficient Colony Robot
  Gary Parker and Richard Zbeda
• Efficient and Safe Path Planning for a Mobile Robot Using Genetic Algorithm
  Mahmood Naderan Tahan and Mohammad Taghi Manzuri-Shalmani
• Robot Design for Space Missions using Evolutionary Computation
  Malte Römmermann, Daniel Kühn and Frank Kirchner

Post Conference Book Publication

Authors of the best selected paper from among those accepted for the “Evolutionary Robotics” session will be invited to submit an extended version for review for possible publication as a chapter in the forthcoming book “The Horizons of Evolutionary Robotics” edited by Patricia A. Vargas, Ezequiel Di Paolo, Inman Harvey and Phil Husbands (publisher MIT Press).

Programme Commitee

Organisers

Patricia A. Vargas Heriot-Watt University

Sabine Hauert EPFL

Dario Floreano EPFL

Phil Husbands University of Sussex