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Paper Citation Record · LEDGER

Multi-Objective Compliance-Integrated Coevolution For Simulated And Real-World Deployment Of Multi-Robot Marine Autonomy

As of 17 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 0 inbound Pith citation observations for arXiv:2607.26279.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2607.26279 v1

Coverage vector

measured 32 of 32 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T00:19:10.186642Z

measured 32 of 32 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

32 of 32 outbound references displayed

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  • verified fuzzy0
  • unresolved30
  • parse uncertain0
  • malformed identifier0
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External citation measurements

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Outbound references

Observation bfd7d3d8-f709-4e15-9809-c7846c02a852 · outbound

This paper cites Washington, DC: U.S.

Multi-Objective Compliance-Integrated Coevolution For Simulated And Real-World Deployment Of Multi-Robot Marine Autonomy Washington, DC: U.S

Reference 1

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Observation e98194db-bffd-454f-9adc-8c6a8c1becc2 · outbound

This paper cites Efficient evaluation functions for multi- rover systems,.

Multi-Objective Compliance-Integrated Coevolution For Simulated And Real-World Deployment Of Multi-Robot Marine Autonomy Efficient evaluation functions for multi- rover systems,

Reference 2

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Observation db52e625-c50b-494c-aeae-4f22fae74cea · outbound

This paper cites Cooperative coevolution: An architecture for evolving coadapted subcomponents,.

Multi-Objective Compliance-Integrated Coevolution For Simulated And Real-World Deployment Of Multi-Robot Marine Autonomy Cooperative coevolution: An architecture for evolving coadapted subcomponents,

Reference 3

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Observation abb80cf6-25aa-46db-8b66-40e15d63a6aa · outbound

This paper cites Environment driven dynamic decomposition for cooperative coevolution of multi-agent systems,.

Multi-Objective Compliance-Integrated Coevolution For Simulated And Real-World Deployment Of Multi-Robot Marine Autonomy Environment driven dynamic decomposition for cooperative coevolution of multi-agent systems,

Reference 4

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Observation 7ee88a7f-77c8-41b2-a88f-6ada81548d92 · outbound

This paper cites Learning autonomous ma- rine behaviors in moos-ivp,.

Multi-Objective Compliance-Integrated Coevolution For Simulated And Real-World Deployment Of Multi-Robot Marine Autonomy Learning autonomous ma- rine behaviors in moos-ivp,

Reference 5

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Observation 0ab3a61c-5742-430c-9dcb-551a42e367bd · outbound

This paper cites Data-driven performance-prescribed reinforcement learning control of an unmanned surface vehicle,.

Multi-Objective Compliance-Integrated Coevolution For Simulated And Real-World Deployment Of Multi-Robot Marine Autonomy Data-driven performance-prescribed reinforcement learning control of an unmanned surface vehicle,

Reference 6

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Observation 071bae2c-58cc-491c-996e-d9e6d438b988 · outbound

This paper cites Learn to navigate: Cooperative path planning for unmanned surface vehicles using deep reinforcement learning,.

Multi-Objective Compliance-Integrated Coevolution For Simulated And Real-World Deployment Of Multi-Robot Marine Autonomy Learn to navigate: Cooperative path planning for unmanned surface vehicles using deep reinforcement learning,

Reference 7

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Observation 22e9debb-3424-4325-946e-ff4d5b55b457 · outbound

This paper cites A sim-to-real transfer framework for enhancing marine vehicle performance in ocean environments,.

Multi-Objective Compliance-Integrated Coevolution For Simulated And Real-World Deployment Of Multi-Robot Marine Autonomy A sim-to-real transfer framework for enhancing marine vehicle performance in ocean environments,

Reference 8

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Observation 83ccaa92-c178-4ae8-834f-7c22b8a93fd8 · outbound

This paper cites Marinegym: A high-performance reinforcement learning platform for underwater robotics,.

Multi-Objective Compliance-Integrated Coevolution For Simulated And Real-World Deployment Of Multi-Robot Marine Autonomy Marinegym: A high-performance reinforcement learning platform for underwater robotics,

Reference 9

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Observation cb5055a8-95f0-4be9-8ac7-4d65ed99016c · outbound

This paper cites an unresolved cited work.

Multi-Objective Compliance-Integrated Coevolution For Simulated And Real-World Deployment Of Multi-Robot Marine Autonomy Unresolved cited work

Reference 10

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Observation 28f005de-04e2-4289-aed0-1fa497b8e38c · outbound

This paper cites Evolutionary reinforcement learning for sparse rewards,.

Multi-Objective Compliance-Integrated Coevolution For Simulated And Real-World Deployment Of Multi-Robot Marine Autonomy Evolutionary reinforcement learning for sparse rewards,

Reference 11

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Observation f25fd0f8-3c6f-42dc-9161-87cbe4ad5d11 · outbound

This paper cites Evolutionary computation for sparse multi-objective optimization: A survey,.

Multi-Objective Compliance-Integrated Coevolution For Simulated And Real-World Deployment Of Multi-Robot Marine Autonomy Evolutionary computation for sparse multi-objective optimization: A survey,

Reference 12

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Observation fc761857-33a1-472d-a9ed-fc06c72100db · outbound

This paper cites D++: Structural credit assignment in tightly coupled multiagent domains,.

Multi-Objective Compliance-Integrated Coevolution For Simulated And Real-World Deployment Of Multi-Robot Marine Autonomy D++: Structural credit assignment in tightly coupled multiagent domains,

Reference 13

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Observation 81608150-75e3-4f29-bdf3-a02a31c03b0e · outbound

This paper cites Global optimal path planning for multi-agent flocking: A multi-objective optimization approach with nsga-iii,.

Multi-Objective Compliance-Integrated Coevolution For Simulated And Real-World Deployment Of Multi-Robot Marine Autonomy Global optimal path planning for multi-agent flocking: A multi-objective optimization approach with nsga-iii,

Reference 14

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Observation 5e1f000e-cc0d-4379-89ef-d48bc89401e5 · outbound

This paper cites Multi-objective multi- criteria evolutionary algorithm for multi-objective multi-task optimiza- tion,.

Multi-Objective Compliance-Integrated Coevolution For Simulated And Real-World Deployment Of Multi-Robot Marine Autonomy Multi-objective multi- criteria evolutionary algorithm for multi-objective multi-task optimiza- tion,

Reference 15

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Observation 656e94a5-b7ac-4847-8496-c8d6649982ba · outbound

This paper cites Multi-usv deep reinforcement learning for distributed cooperative target tracking,.

Multi-Objective Compliance-Integrated Coevolution For Simulated And Real-World Deployment Of Multi-Robot Marine Autonomy Multi-usv deep reinforcement learning for distributed cooperative target tracking,

Reference 16

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Observation d5ef64a6-b825-485f-987b-26dd10eb9574 · outbound

This paper cites Autonomous environmental exploration and target tracking control for unmanned surface vehicles in uncertain environment,.

Multi-Objective Compliance-Integrated Coevolution For Simulated And Real-World Deployment Of Multi-Robot Marine Autonomy Autonomous environmental exploration and target tracking control for unmanned surface vehicles in uncertain environment,

Reference 17

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Observation c0b5b584-b5c2-4f51-b246-8403aff4c7dd · outbound

This paper cites Cooperative target fencing of uncertain multi-usvs: A reinforcement learning-based approach,.

Multi-Objective Compliance-Integrated Coevolution For Simulated And Real-World Deployment Of Multi-Robot Marine Autonomy Cooperative target fencing of uncertain multi-usvs: A reinforcement learning-based approach,

Reference 18

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Observation 38ae7bb5-f7fb-47fd-9702-ab6dc8c58dfc · outbound

This paper cites Evaluating Collaborative Autonomy in Opposed Environments using Maritime Capture-the-Flag Competitions.

Multi-Objective Compliance-Integrated Coevolution For Simulated And Real-World Deployment Of Multi-Robot Marine Autonomy Evaluating Collaborative Autonomy in Opposed Environments using Maritime Capture-the-Flag Competitions

Reference 19

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Observation eb8f4966-0412-4b16-ba9a-2fa5baf0dd76 · outbound

This paper cites Nested autonomy for unmanned marine vehicles with moos-ivp,.

Multi-Objective Compliance-Integrated Coevolution For Simulated And Real-World Deployment Of Multi-Robot Marine Autonomy Nested autonomy for unmanned marine vehicles with moos-ivp,

Reference 20

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Observation 2d142828-2687-4617-a2b4-fceb558cfba6 · outbound

This paper cites A study on the effectiveness of moos-ivp for unmanned surface vehicle,.

Multi-Objective Compliance-Integrated Coevolution For Simulated And Real-World Deployment Of Multi-Robot Marine Autonomy A study on the effectiveness of moos-ivp for unmanned surface vehicle,

Reference 21

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Observation dbed395d-817a-4936-a367-c9c96670a89e · outbound

This paper cites Moos-ivp avdcolregs behavior,.

Multi-Objective Compliance-Integrated Coevolution For Simulated And Real-World Deployment Of Multi-Robot Marine Autonomy Moos-ivp avdcolregs behavior,

Reference 22

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Observation 359fa2a1-8db1-4e0c-8294-53bcf5e86cb9 · outbound

This paper cites Moos-ivp opregion behavior,.

Multi-Objective Compliance-Integrated Coevolution For Simulated And Real-World Deployment Of Multi-Robot Marine Autonomy Moos-ivp opregion behavior,

Reference 23

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Observation 247ea069-c0b9-44ea-b912-d166ef98ed57 · outbound

This paper cites Safety-critical model-free control for multi-target tracking of usvs with collision avoidance,.

Multi-Objective Compliance-Integrated Coevolution For Simulated And Real-World Deployment Of Multi-Robot Marine Autonomy Safety-critical model-free control for multi-target tracking of usvs with collision avoidance,

Reference 24

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Observation 5f5f12e9-5ff9-4ca3-8a4e-fc108a9eed82 · outbound

This paper cites Coordinated landing control for cross-domain uav-usv fleets using heterogeneous-feature matching,.

Multi-Objective Compliance-Integrated Coevolution For Simulated And Real-World Deployment Of Multi-Robot Marine Autonomy Coordinated landing control for cross-domain uav-usv fleets using heterogeneous-feature matching,

Reference 25

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Observation c3dd0785-7e15-4bc8-a671-b86827544e5d · outbound

This paper cites A robust layered control system for a mobile robot,.

Multi-Objective Compliance-Integrated Coevolution For Simulated And Real-World Deployment Of Multi-Robot Marine Autonomy A robust layered control system for a mobile robot,

Reference 26

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Observation 106e091b-0e95-498a-bae8-b481fb154443 · outbound

This paper cites Control barrier function based quadratic programs for safety critical systems,.

Multi-Objective Compliance-Integrated Coevolution For Simulated And Real-World Deployment Of Multi-Robot Marine Autonomy Control barrier function based quadratic programs for safety critical systems,

Reference 27

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Observation 89d3ed8d-2369-4b35-945d-a771a03bcde7 · outbound

This paper cites an unresolved cited work.

Multi-Objective Compliance-Integrated Coevolution For Simulated And Real-World Deployment Of Multi-Robot Marine Autonomy Unresolved cited work

Reference 28

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Observation dec471be-20b5-45c5-9fda-238fdc9c274a · outbound

This paper cites Fullest colregs evaluation using fuzzy logic for collaborative decision-making analysis of autonomous ships in complex situations,.

Multi-Objective Compliance-Integrated Coevolution For Simulated And Real-World Deployment Of Multi-Robot Marine Autonomy Fullest colregs evaluation using fuzzy logic for collaborative decision-making analysis of autonomous ships in complex situations,

Reference 29

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Observation 37a4cce9-d15c-4ff7-8329-08c80e2e8aa2 · outbound

This paper cites Gonzalez, G.

Multi-Objective Compliance-Integrated Coevolution For Simulated And Real-World Deployment Of Multi-Robot Marine Autonomy Gonzalez, G

Reference 31

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Observation 74afa491-b0d8-405d-9012-0332f597a649 · outbound

This paper cites Adversarial resilience for sampled-data systems using control barrier function methods,.

Multi-Objective Compliance-Integrated Coevolution For Simulated And Real-World Deployment Of Multi-Robot Marine Autonomy Adversarial resilience for sampled-data systems using control barrier function methods,

Reference 32

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Observation 50d4fa19-9680-4b6b-b0e1-5ee14681a8b8 · outbound

This paper cites Available: https://doi.org/10.1145/3734865.

Multi-Objective Compliance-Integrated Coevolution For Simulated And Real-World Deployment Of Multi-Robot Marine Autonomy Available: https://doi.org/10.1145/3734865

Reference 2025

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Pith citing papers

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