Navigation for social organisms rarely is a fully independent activity. Group structure and dynamics, as well as embodied interactions, critically influence useful behavior. Individual neural network. Based on arXiv:2607.07460.
Scanned 9/11/2026
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---
name: social-spatial-dependencies-for-learning-visual-navigation
description: 'Navigation for social organisms rarely is a fully independent activity. Group structure and dynamics, as well as embodied interactions, critically influence useful behavior. Individual neural network. Based on arXiv:2607.07460.'
---
# Social-spatial dependencies for learning visual navigation
**arXiv**: 2607.07460 | **Authors**: Patrick Govoni, Pawel Romanczuk | **Utility**: 0.85
## Overview
Navigation for social organisms rarely is a fully independent activity. Group structure and dynamics, as well as embodied interactions, critically influence useful behavior. Individual neural network controlled agents are trained to navigate in different social contexts, where social dependence and behavioral strategy learned is determined by relative task performance and spatial effect. Increasing high quality social information drives phase transitions from individual to following navigational strategy, and to collision avoidance in response to a crowded foraging patch. Predictable, nonstationary environmental dynamics drive behavioral hybridization between individual and social navigation, far and near the patch. Our findings challenge the approach of only inspecting individual behavior for social organisms and highlight the importance of taking a bottom-up approach in understanding how organisms behave.
## Key Contributions
1. Navigation for social organisms rarely is a fully independent activity.
2. Group structure and dynamics, as well as embodied interactions, critically influence useful behavior.
3. Individual neural network controlled agents are trained to navigate in different social contexts, where social dependence and behavioral strategy learned is determined by relative task performance and spatial effect.
4. Increasing high quality social information drives phase transitions from individual to following navigational strategy, and to collision avoidance in response to a crowded foraging patch.
## Implementation Notes
- **Keywords**: control-systems, neural-network, embodied-ai, social-agent
- **Categories**: cs.NE
- **Published**: 2026-07-08
## Activation Criteria
Use this skill when working on tasks involving: control-systems, neural-network, embodied-ai, social-agent.
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