LLMs for Text-Based Exploration and Navigation Under Partial Observability
Exploration and goal-directed navigation in unknown layouts are central to inspection, logistics, and search-and-rescue. We ask whether large language models (LLMs) can function as \emph{text-only} controllers under partial observability -- without code execution, tools, or program synthesis. We introduce a reproducible benchmark with oracle localisation in fixed ASCII gridworlds: each step reveals only a local $5\times5$ window around the agent and the model must select one of \texttt{UP/RIGHT/DOWN/LEFT}. Nine contemporary LLMs ranging from open/proprietary, dense / Mixture of Experts and instruction- vs. reasoning-tuned are evaluated on two tasks across three layouts of increasing diffi...
| Authors | Stephan Sandfuchs, Maximilian Melchert, Jörg Frochte |
|---|---|
| Primary category | cs.AI |
| Published | 10 March 2026 |
| Last updated at source | 10 March 2026 |
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