Self-perturbation and Homeostasis in Embodied Recurrent Neural Networks: A Meta-model and Some Explorations with Mechanisms for

Abstract. We present a model of a recurrent neural network, embodied in a minimalist articulated agent with a single link and joint. The configuration of the agent defined by one angle (degree of freedom), is determined by the activation state of the neural network. This is done by contracting a muscle with many muscular fibers, whose contraction state needs to be coordinated to generate high amplitude link displacements. In networks without homeostasic (self-regulatory) mechanism the neural state dynamics and the configuration state dynamics converges to a fixed

• Type: Conference
• Year: 2007
• Where: ICANN
• Authors: Jorge Simão
• Keywords: ICANN 2007, Minimalist Articulated Agent, Neural Network, Recurrent Neural Network