pith:6IN5AO3B
Task-Semantic Graph-Driven Distributed Agent Networking for Underwater Target Tracking
An open MARL platform with a semantic task graph lets AUV swarms track moving targets under acoustic constraints and limited observations.
arxiv:2605.15528 v1 · 2026-05-15 · cs.RO · cs.MA
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Claims
To the best of our knowledge, it is the first open platform that connects a public MARL training framework with physically modeled AUV swarm-based tasks, and provides a unified experimental protocol for fair training, testing, and comparison of representative RL and MARL algorithms. Based on this platform, we propose STG-MAPPO, a Semantic Task Graph-enhanced variant of Multi-Agent Proximal Policy Optimization.
The integration of DI-engine with a six-degree-of-freedom underwater AUV target-tracking simulator produces a sufficiently accurate and representative model of real acoustic constraints, observation limits, and vehicle dynamics to support valid comparisons of MARL algorithms for persistent tracking.
Develops an open-source MARL-AUV platform integrating DI-engine with 6DOF AUV simulation and proposes STG-MAPPO using semantic task graphs for distributed underwater target tracking.
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| First computed | 2026-05-20T00:01:03.541298Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
f21bd03b61ec5414111fcda215f0ed4594fbe2b83777521b68d6dfdd611002ef
Aliases
· · · · ·Agent API
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curl -sH 'Accept: application/ld+json' https://pith.science/pith/6IN5AO3B5RKBIEI7ZWRBL4HNIW \
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Canonical record JSON
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