The special issue of Artificial Life on Embodied Intelligence is now live! Inside you will find our paper "Braitenberg Vehicles as Developmental Neurosimulation", which has lived on the arXiv since 2020. This paper lays out an approach to Developmental Neurosimulation, involving three adversarial approaches to the agent-based development of embodied brains and embodied cognition. Here is the abstract:
Connecting brain and behavior is a longstanding issue in the areas of behavioral science, artificial intelligence, and neurobiology. As is standard among models of artificial and biological neural networks, an analogue of the fully mature brain is presented as a blank slate. However, this does not consider the realities of biological development and developmental learning. Our purpose is to model the development of an artificial organism that exhibits complex behaviors. We introduce three alternate approaches to demonstrate how developmental embodied agents can be implemented. The resulting developmental Braitenberg vehicles (dBVs) will generate behaviors ranging from stimulus responses to group behavior that resembles collective motion. We will situate this work in the domain of artificial brain networks along with broader themes such as embodied cognition, feedback, and emergence. Our perspective is exemplified by three software instantiations that demonstrate how a BV-genetic algorithm hybrid model, a multisensory Hebbian learning model, and multi-agent approaches can be used to approach BV development. We introduce use cases such as optimized spatial cognition (vehicle-genetic algorithm hybrid model), hinges connecting behavioral and neural models (multisensory Hebbian learning model), and cumulative classification (multi-agent approaches). In conclusion, we consider future applications of the developmental neurosimulation approach.
There are many themes to follow up on in this paper. Just of few examples include:
* brain/body scaling in an embodied agent.
* the role of multisensory integration in the development of cognition.
* ways to classify shapes and motifs in the emergence of multi-agent collectives.
* spatial cognition and transfer learning in developmental embodied systems.
Congratulations to Stefan Dvoretskii, Ziyi Gong, Ankit Gupta, Jesse Parent, and Bradly Alicea for their hard work.
