Explorations in evolutionary robotics
Adaptive Behavior
Genetic programming II: automatic discovery of reusable programs
Genetic programming II: automatic discovery of reusable programs
Integrating reactive, sequential, and learning behavior using dynamical neural networks
SAB94 Proceedings of the third international conference on Simulation of adaptive behavior : from animals to animats 3: from animals to animats 3
Seeing the light: artificial evolution, real vision
SAB94 Proceedings of the third international conference on Simulation of adaptive behavior : from animals to animats 3: from animals to animats 3
Automatic creation of an autonomous agent: genetic evolution of a neural-network driven robot
SAB94 Proceedings of the third international conference on Simulation of adaptive behavior : from animals to animats 3: from animals to animats 3
Learning and evolution in neural networks
Adaptive Behavior
Discontinuity in evolution: how different levels of organization imply preadaptation
Adaptive individuals in evolving populations
Noise and the Reality Gap: The Use of Simulation in Evolutionary Robotics
Proceedings of the Third European Conference on Advances in Artificial Life
Mobile Robot Miniaturisation: A Tool for Investigation in Control Algorithms
The 3rd International Symposium on Experimental Robotics III
Selection for wandering behavior in a small robot
Artificial Life
Evolution of Neural Controllers with Adaptive Synapses and Compact Genetic Encoding
ECAL '99 Proceedings of the 5th European Conference on Advances in Artificial Life
Robot Learning Using Gate-Level Evolvable Hardware
EWLR-6 Proceedings of the 6th European Workshop on Learning Robots
Learning Complex Robot Behaviours by Evolutionary Computing with Task Decomposition
EWLR-6 Proceedings of the 6th European Workshop on Learning Robots
EWLR-8 Proceedings of the 8th European Workshop on Learning Robots: Advances in Robot Learning
Evolutionary Robots with Fast Adaptive Behaviour in New Environments
ICES '00 Proceedings of the Third International Conference on Evolvable Systems: From Biology to Hardware
Evolution of Controllers from a High-Level Simulator to a High DOF Robot
ICES '00 Proceedings of the Third International Conference on Evolvable Systems: From Biology to Hardware
Robot Soccer with LEGO Mindstorms
RoboCup-98: Robot Soccer World Cup II
Simulation of Nest Assessment Behavior by Ant Scouts
ANTS '02 Proceedings of the Third International Workshop on Ant Algorithms
ECAL '99 Proceedings of the 5th European Conference on Advances in Artificial Life
Anticipatory Behavior in Adaptive Learning Systems
Navigation in Evolving Robots: Insight from Vertebrates
AI*IA '09: Proceedings of the XIth International Conference of the Italian Association for Artificial Intelligence Reggio Emilia on Emergent Perspectives in Artificial Intelligence
Exploring the T-Maze: evolving learning-like robot behaviors using CTRNNs
EvoWorkshops'03 Proceedings of the 2003 international conference on Applications of evolutionary computing
Co-evolving complex robot behavior
ICES'03 Proceedings of the 5th international conference on Evolvable systems: from biology to hardware
Evolving reinforcement learning-like abilities for robots
ICES'03 Proceedings of the 5th international conference on Evolvable systems: from biology to hardware
Discovering several robot behaviors through speciation
Evo'08 Proceedings of the 2008 conference on Applications of evolutionary computing
Crossing the reality gap in evolutionary robotics by promoting transferable controllers
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Proceedings of the 13th annual conference on Genetic and evolutionary computation
How to promote generalisation in evolutionary robotics: the ProGAb approach
Proceedings of the 13th annual conference on Genetic and evolutionary computation
For corvids together is better: a model of cooperation in evolutionary robotics
ECAL'09 Proceedings of the 10th European conference on Advances in artificial life: Darwin meets von Neumann - Volume Part I
Evolving robot's behavior by using CNNs
SAB'06 Proceedings of the 9th international conference on From Animals to Animats: simulation of Adaptive Behavior
EELC'06 Proceedings of the Third international conference on Emergence and Evolution of Linguistic Communication: symbol Grounding and Beyond
Landau theory of meta-learning
SIIS'11 Proceedings of the 2011 international conference on Security and Intelligent Information Systems
A comparison of sampling strategies for parameter estimation of a robot simulator
SIMPAR'12 Proceedings of the Third international conference on Simulation, Modeling, and Programming for Autonomous Robots
An evolutionary approach for robust adaptation of robot behavior to sensor error
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
Communications of the ACM
Architecture of a cyberphysical avatar
Proceedings of the ACM/IEEE 4th International Conference on Cyber-Physical Systems
Encouraging reactivity to create robust machines
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
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The problem of the validity of simulation is particularly relevant for methodologies that use machine learning techniques to develop control systems for autonomous robots, as, for instance, the artificial life approach known as evolutionary robotics. In fact, although it has been demonstrated that training or evolving robots in real environments is possible, the number of trials needed to test the system discourages the use of physical robots during the training period. By evolving neural controllers for a Khepera robot in computer simulations and then transferring the agents obtained to the real environment we show that (a) an accurate model of a particular robot-environment dynamics can be built by sampling the real world through the sensors and the actuators of the robot; (b) the performance gap between the obtained behaviors in simulated and real environments may be significantly reduced by introducing a "conservative" form of noise; (c) if a decrease in performance is observed when the system is transferred to a real environment, successful and robust results can be obtained by continuing the evolutionary process in the real environment for a few generations.