Visuospatial Navigation Algorithms
Published in arxiv, 2025
PhD Thesis - Part One. Visual-motor learning of artificial neural networks.
Author: Patrick Govoni
Supervisor: Pawel Romanczuk
Affiliation: Institute for Theoretical Biology, Humboldt Universität zu Berlin
Group: Collective Information Processing Lab
Years: 2023-Present
Preprint
Github Repo
Talk @ ScioI Summer School 2023
Talk @ ALife 2024
Extended Abstract @ ALife 2024
Abstract:
Navigation is controlled by at least two partially dissociable, concurrently developed systems in the brain. The cognitive map informs an organism of its location and bearing, updated by distance-based prediction and vestibular integration. Response-based systems, on the other hand, directly evaluate movement decisions from immediate percepts. Here we demonstrate the sufficiency of visual response-based decision-making in a classic open field navigation task often assumed to require a cognitive map. Three distinct strategies emerge to robustly navigate to a hidden goal, each conferring contextual tradeoffs, as well as aligning with behavior observed with rodents, insects, fish, and sperm cells. We propose reframing navigation from the bottom-up, without assuming online access to computationally expensive top-down representations, to better explain behavior under energetic or attentional constraints.