# A Knowledge-Graph Translation Layer for Mission-Aware Multi-Agent Path Planning in Spatiotemporal Dynamics

arXiv: https://arxiv.org/abs/2510.21695 · HTML: https://mlsanity.com/paper/2510.21695/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 5 of its 35 references that are in the map.
- First posted on arXiv 24 Oct 2025.

## Builds on (most cited first, 5 of 5)

- [A Stochastic Geo-spatiotemporal Bipartite Network to Optimize GCOOS Sensor Placement Strategies](https://mlsanity.com/paper/2404.14357/) (2024)
- [STROOBnet Optimization via GPU-Accelerated Proximal Recurrence Strategies](https://mlsanity.com/paper/2404.14388/) (2024)
- [Choreographing the Rhythms of Observation: Dynamics for Ranged Observer Bipartite-Unipartite SpatioTemporal (ROBUST) Networks](https://mlsanity.com/paper/2406.07473/) (2024)
- [Data Visualization to Evaluate and Facilitate Targeted Data Acquisitions in Support of a Real-time Ocean Forecasting System](https://mlsanity.com/paper/2409.13907/) (2024)
- [Knowledge Graph-Based Multi-Agent Path Planning in Dynamic Environments using WAITR](https://mlsanity.com/paper/2412.19469/) (2024)

## Abstract (arXiv)

The coordination of autonomous agents in dynamic environments is hampered by the semantic gap between high-level mission objectives and low-level planner inputs. To address this, we introduce a framework centered on a Knowledge Graph (KG) that functions as an intelligent translation layer. The KG's two-plane architecture compiles declarative facts into per-agent, mission-aware ``worldviews" and physics-aware traversal rules, decoupling mission semantics from a domain-agnostic planner. This allows complex, coordinated paths to be modified simply by changing facts in the KG. A case study involving Autonomous Underwater Vehicles (AUVs) in the Gulf of Mexico visually demonstrates the end-to-end process and quantitatively proves that different declarative policies produce distinct, high-performing outcomes. This work establishes the KG not merely as a data repository, but as a powerful, stateful orchestrator for creating adaptive and explainable autonomous systems.