Memory & Planning Excel in Dynamic Navigation
This arXiv paper explores memory strategies for spatial navigation in non-stationary environments with uncertain sensing in a foraging task. It compares simple to sophisticated agents, finding hybrid architectures with episodic memories and on-the-fly planning most efficient for exploration, search, and path optimization. Advanced agents substantially outperform minimal-memory ones as task difficulty increases, provided uncertainty is manageable.






