Analog VLSI and neural systems
Analog VLSI and neural systems
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations
Associative memory in a network of biological neurons
NIPS-3 Proceedings of the 1990 conference on Advances in neural information processing systems 3
Evolving dynamical neural networks for adaptive behavior
Adaptive Behavior
Pulsed neural networks
Evolutionary Robotics: The Biology,Intelligence,and Technology
Evolutionary Robotics: The Biology,Intelligence,and Technology
Autonomous Vehicle Guidance Using Analog VLSI Neuromorphic Sensors
ICANN '97 Proceedings of the 7th International Conference on Artificial Neural Networks
What matters in neuronal locking?
Neural Computation
A neuromorphic VLSI device for implementing 2D selective attention systems
IEEE Transactions on Neural Networks
Evolving Vision-Based Flying Robots
BMCV '02 Proceedings of the Second International Workshop on Biologically Motivated Computer Vision
Evolution of a circuit of spiking neurons for phototaxis in a Braitenberg vehicle
ICSAB Proceedings of the seventh international conference on simulation of adaptive behavior on From animals to animats
ICAL 2003 Proceedings of the eighth international conference on Artificial life
Evolutionary Computation - Special issue on magnetic algorithms
From Wheels to Wings with Evolutionary Spiking Circuits
Artificial Life
Learning Beyond Finite Memory in Recurrent Networks of Spiking Neurons
Neural Computation
Evolutionary morphogenesis for multi-cellular systems
Genetic Programming and Evolvable Machines
Evolving networks of integrate-and-fire neurons
Neurocomputing
Stochastic training of a biologically plausible spino-neuromuscular system model
Proceedings of the 9th annual conference on Genetic and evolutionary computation
A Simple Aplysia-Like Spiking Neural Network to Generate Adaptive Behavior in Autonomous Robots
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
Adaptive Olfactory Encoding in Agents Controlled by Spiking Neural Networks
SAB '08 Proceedings of the 10th international conference on Simulation of Adaptive Behavior: From Animals to Animats
Learning anticipation via spiking networks: application to navigation control
IEEE Transactions on Neural Networks
Evolving Spiking Neural Parameters for Behavioral Sequences
ICANN '09 Proceedings of the 19th International Conference on Artificial Neural Networks: Part II
Evolving spiking neuron controllers for phototaxis and phonotaxis
EvoWorkshops'03 Proceedings of the 2003 international conference on Applications of evolutionary computing
Using spiking neural networks for the generation of coordinated action sequences in robots
ICONIP'08 Proceedings of the 15th international conference on Advances in neuro-information processing - Volume Part I
Spike-Timing dependent plasticity learning for visual-based obstacles avoidance
SAB'06 Proceedings of the 9th international conference on From Animals to Animats: simulation of Adaptive Behavior
Spiking neural controllers for pushing objects around
SAB'06 Proceedings of the 9th international conference on From Animals to Animats: simulation of Adaptive Behavior
A target-reaching controller for mobile robots using spiking neural networks
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part IV
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We describe a set of preliminary experiments to evolve spiking neural controllers for a vision-based mobile robot. All the evolutionary experiments are carried out on physical robots without human intervention. After discussing how to implement and interface these neurons with a physical robot, we show that evolution finds relatively quickly functional spiking controllers capable of navigating in irregularly textured environments without hitting obstacles using a very simple genetic encoding and fitness function. Neuroethological analysis of the network activity let us understand the functioning of evolved controllers and tell the relative importance of single neurons independently of their observed firing rate. Finally, a number of systematic lesion experiments indicate that evolved spiking controllers are very robust to synaptic strength decay that typically occurs in hardware implementations of spiking circuits.