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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.<\/jats:p>","DOI":"10.1162\/artl_a_00384","type":"journal-article","created":{"date-parts":[[2022,7,26]],"date-time":"2022-07-26T17:56:48Z","timestamp":1658858208000},"page":"369-395","update-policy":"https:\/\/doi.org\/10.1162\/mitpressjournals.corrections.policy","source":"Crossref","is-referenced-by-count":6,"title":["Braitenberg Vehicles as Developmental Neurosimulation"],"prefix":"10.1162","volume":"28","author":[{"given":"Stefan","family":"Dvoretskii","sequence":"first","affiliation":[{"name":"Technical University of Munich"}]},{"given":"Ziyi","family":"Gong","sequence":"additional","affiliation":[{"name":"Duke University"}]},{"given":"Ankit","family":"Gupta","sequence":"additional","affiliation":[{"name":"Taipei Medical University"}]},{"given":"Jesse","family":"Parent","sequence":"additional","affiliation":[{"name":"Orthogonal Research and Education 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