Intelligence as adaptive behavior: an experiment in computational neuroethology
Intelligence as adaptive behavior: an experiment in computational neuroethology
On What Makes Certain Dynamical Systems Cognitive: A Minimally Cognitive Organization Program
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
Toward Spinozist Robotics: Exploring the Minimal Dynamics of Behavioral Preference
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
Enactive artificial intelligence: Investigating the systemic organization of life and mind
Artificial Intelligence
A dynamical systems perspective on agent-environment interaction
Artificial Intelligence
New models for old questions: evolutionary robotics and the 'A not B' error
ECAL'07 Proceedings of the 9th European conference on Advances in artificial life
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This study presents an extended dynamic neural network model of homeostatic adaptation as the first step toward constructing a model of mental imagery. In the homeostatic adaptation model, higher-level dynamics internally self-organized from sensorimotor dynamics are associated with desired behaviors. These dynamics are regenerated when drastic changes occur, which might break the internal dynamics. Due to the weak link between desired behavior and internal homeostasis in the original homeostatic adaptation model, adaptivity is limited. In this paper, we improve on the homeostatic adaptation model to create a stronger link between desired behavior and internal homeostasis by introducing a metabolic causation in a plasticity mechanism and show that it becomes more adaptive. Our results show that our model has three different time scales in the adaptive behaviors, which are discussed with our cognition and mental imagery.