Artificial Intelligence
Computational neuroethology: a provisional manifesto
Proceedings of the first international conference on simulation of adaptive behavior on From animals to animats
Adding “foveal vision” to Wilson's animat
Adaptive Behavior
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
Modeling visual attention via selective tuning
Artificial Intelligence - Special volume on computer vision
Embedded neural networks: exploiting constraints
Neural Networks - Special issue on neural control and robotics: biology and technology
Understanding intelligence
Evolutionary Robotics: The Biology,Intelligence,and Technology
Evolutionary Robotics: The Biology,Intelligence,and Technology
Evolving neural networks through augmenting topologies
Evolutionary Computation
Knowledge Growth in an Artificial Animal
Proceedings of the 1st International Conference on Genetic Algorithms
The world from a cat’s perspective – statistics of natural videos
Biological Cybernetics
Coevolution of active vision and feature selection
Biological Cybernetics
Active Vision and Receptive Field Development in Evolutionary Robots
Evolutionary Computation
Neural Networks - 2005 Special issue: IJCNN 2005
VOCUS: A Visual Attention System for Object Detection and Goal-Directed Search (Lecture Notes in Computer Science / Lecture Notes in Artificial Intelligence)
Evolutionary active vision toward three dimensional landmark-navigation
SAB'06 Proceedings of the 9th international conference on From Animals to Animats: simulation of Adaptive Behavior
Analog Genetic Encoding for the Evolution of Circuits and Networks
IEEE Transactions on Evolutionary Computation
Enactive artificial intelligence: Investigating the systemic organization of life and mind
Artificial Intelligence
The Cognitive Body: From Dynamic Modulation to Anticipation
Anticipatory Behavior in Adaptive Learning Systems
SAB'10 Proceedings of the 11th international conference on Simulation of adaptive behavior: from animals to animats
Towards active event recognition
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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Enactivism claims that sensory-motor activity and embodiment are crucial in perceiving the environment and that machine vision could be a much simpler business if considered in this context. However, computational models of enactive vision are very rare and often rely on handcrafted control systems. In this article, we argue that the apparent complexity of the environment and of the robot brain can be significantly simplified if perception, behavior, and learning are allowed to co-develop on the same timescale. In doing so, robots become sensitive to, and actively exploit, characteristics of the environment that they can tackle within their own computational and physical constraints. We describe the application of this methodology in three sets of experiments: shape discrimination, car driving, and wheeled robot navigation. A further set of experiments, where the visual system can develop the receptive fields by means of unsupervised Hebbian learning, demonstrates that the receptive fields are consistently and significantly affected by the behavior of the system and differ from those predicted by most computational models of the visual cortex. Finally, we show that our robots can also replicate the performance deficiencies observed in experiments of motor deprivation with kittens.