Flexible Couplings: Diffusing Neuromodulators and Adaptive Robotics

Abstract

Recent years have seen the discovery of freely diffusing gaseous neurotransmitters, such as nitric oxide (NO), in biological nervous systems. A type of artificial neural network (ANN) inspired by such gaseous signaling, the GasNet, has previously been shown to be more evolvable than traditional ANNs when used as an artificial nervous system in an evolutionary robotics setting, where evolvability means consistent speed to very good solutions--here, appropriate sensorimotor behavior-generating systems. We present two new versions of the GasNet, which take further inspiration from the properties of neuronal gaseous signaling. The plexus model is inspired by the extraordinary NO-producing cortical plexus structure of neural fibers and the properties of the diffusing NO signal it generates. The receptor model is inspired by the mediating action of eurotransmitter receptors. Both models are shown to significantly further improve evolvability. We describe a series of analyses suggesting that the reasons for the increase in evolvability are related to the flexible loose coupling of distinct signaling mechanisms, one "chemical" and one "electrical."

The Evolution of Reaction-Diffusion Controllers for Minimally Cognitive Agents

“…As far as we know, this is the first example of an evolved RD-based agent control system, although there has been previous work on evolved neurocontrollers that incorporated a model of diffusing neuromodulators [30,38]. However, that work made use of a very abstract model of diffusion and cannot be regraded as an RD system proper.…”

Evolutionary Robotics

“…Successful GasNet controllers for this task tended to be rather minimal, in terms of numbers of nodes and connections, while possessing complex dynamics [58]. Later experiments comparing the basic GasNet with the plexus and receptor variants showed the latter two to be considerably more evolvable than the former, with the receptor GasNet being particularly successful [95].…”

“…A number of GasNet variants, inspired by different aspects of real nervous systems, have been explored in an evolutionary robotics context as artificial nervous systems for mobile autonomous robots. They have been shown to be significantly more evolvable, in terms of speed to a good solution, than other forms of neural networks for a variety of robot tasks and behaviors [58,79,108,95]. They are being investigated as potentially useful engineering tools and as a way of gaining helpful insights into biological systems [93,94,96].…”

“…In the plexus GasNet, which models this form of signaling at an abstract level, the spatial distribution of gas concentration has been modified to be uniform over the area of affect. The center of this gas diffusion cloud is under genetic control and can be distant from the controlling node (which, by analogy, is the source of the 'plexus') [95]. All other details of the models are identical to the original GasNet model, as described earlier.…”

“…In the original GasNet, any node that was in the path of a diffusing transmitter would be modulated in a fixed way. The receptor model allows site specific modulations, including no modulation (no receptors) and multiple modulations at a single site (see [95] for further details).…”