Neural Networks - Special issue on organisation of computation in brain-like systems
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Being There: Putting Brain, Body, and World Together Again
Being There: Putting Brain, Body, and World Together Again
Cybernetics, Second Edition: or the Control and Communication in the Animal and the Machine
Cybernetics, Second Edition: or the Control and Communication in the Animal and the Machine
Neural Networks - 2006 Special issue: The brain mechanisms of imitation learning
Energetically autonomous robots: Food for thought
Autonomous Robots
Parameter space structure of continuous-time recurrent neural networks
Neural Computation
Adaptive mixtures of local experts
Neural Computation
On Cognition as Dynamical Coupling: An Analysis of Behavioral Attractor Dynamics
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
Dynamical Systems Account for Meta-level Cognition
SAB '08 Proceedings of the 10th international conference on Simulation of Adaptive Behavior: From Animals to Animats
Benefits of Anticipations in Cognitive Agents
The Challenge of Anticipation
An analysis of behavioral attractor dynamics
ECAL'07 Proceedings of the 9th European conference on Advances in artificial life
Self-organization of behavioral primitives as multiple attractor dynamics: A robot experiment
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
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Starting from the situated and embodied perspective on the study of cognition as a source of inspiration, this paper programmatically outlines a path towards an experimental exploration of the role of the body in a minimal anticipatory cognitive architecture. Cognition is here conceived and synthetically analyzed as a broadly extended and distributed dynamic process emerging from the interplay between a body, a nervous system and their environment. Firstly, we show how a non-neural internal state, crucially characterized by slowly changing dynamics, can modulate the activity of a simple neurocontroller. The result, emergent from the use of a standard evolutionary robotic simulation, is a self-organized, dynamic action selection mechanism, effectively operating in a context dependent way. Secondly, we show how these characteristics can be exploited by a novel minimalist anticipatory cognitive architecture. Rather than a direct causal connection between the anticipation process and the selection of the appropriate behavior, it implements a model for dynamic anticipation that operates via bodily mediation (bodily-anticipation hypothesis ). This allows the system to swiftly scale up to more complex tasks never experienced before, achieving flexible and robust behavior with minimal adaptive cost.