A dynamical systems perspective on agent-environment interaction
Artificial Intelligence - Special volume on computational research on interaction and agency, part 1
On the dynamics of small continuous-time recurrent neural networks
Adaptive Behavior - Special issue on computational neuroethology
Multiple paired forward and inverse models for motor control
Neural Networks - Special issue on neural control and robotics: biology and technology
Understanding intelligence
Neural Networks - Special issue on organisation of computation in brain-like systems
Being There: Putting Brain, Body, and World Together Again
Being There: Putting Brain, Body, and World Together Again
Evolutionary Robotics: The Biology,Intelligence,and Technology
Evolutionary Robotics: The Biology,Intelligence,and Technology
Mobile Robot Miniaturisation: A Tool for Investigation in Control Algorithms
The 3rd International Symposium on Experimental Robotics III
An evolved agent performing efficient path integration based homing and search
ECAL'05 Proceedings of the 8th European conference on Advances in Artificial Life
Evolution of homing navigation in a real mobile robot
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Map-based navigation in mobile robots
Cognitive Systems Research
Emergence of an internal model in evolving robots subjected to sensory deprivation
SAB'10 Proceedings of the 11th international conference on Simulation of adaptive behavior: from animals to animats
Evolution of self-organised path formation in a swarm of robots
ANTS'10 Proceedings of the 7th international conference on Swarm intelligence
Active categorical perception of object shapes in a simulated anthropomorphic robotic arm
IEEE Transactions on Evolutionary Computation
On the dynamics of active categorisation of different objects shape through tactile sensors
ECAL'09 Proceedings of the 10th European conference on Advances in artificial life: Darwin meets von Neumann - Volume Part I
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In this article we describe how a population of evolving robots can autonomously develop forms of spatial representation which allow them to self-localize and to discriminate different locations of their environment by integrating sensory-motor information over time. The evolving robots also display a remarkable ability to generalize their skill in new environmental conditions that they have never experienced before. The analysis of the obtained results indicates that the evolved robots come up with simple and robust solutions that exploit quasi-periodic limit cycle dynamics emerging from the coupling between the robot/environmental dynamics and a robot's internal dynamics. More specifically, the variations of a robot's internal states are governed by transient dynamical processes originating from the fact that these internal states tend to slowly approximate fixed attractor points, corresponding to different types of sensory states that last for a limited time duration and alternate while the robot moves in the environment.