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Joint trajectory and offloading optimization in UAV-assisted MEC via federated multi-agent reinforcement learning and potential fields

PaperCitations, authors & open-access status

Joint trajectory and offloading optimization in UAV-assisted MEC via federated multi-agent reinforcement learning and potential fields is a paper indexed in ScholarIQ from OpenAlex.

How many citations does Joint trajectory and offloading optimization in UAV-assisted MEC via federated multi-agent reinforcement learning and potential fields have?

ScholarIQcitation count

Joint trajectory and offloading optimization in UAV-assisted MEC via federated multi-agent reinforcement learning and potential fields has 10 citations in the OpenAlex counts ScholarIQ stores.

When was Joint trajectory and offloading optimization in UAV-assisted MEC via federated multi-agent reinforcement learning and potential fields published?

ScholarIQyear

Joint trajectory and offloading optimization in UAV-assisted MEC via federated multi-agent reinforcement learning and potential fields has 2025 year in the ScholarIQ index.

What is the open-access status of Joint trajectory and offloading optimization in UAV-assisted MEC via federated multi-agent reinforcement learning and potential fields?

ScholarIQoa status

Joint trajectory and offloading optimization in UAV-assisted MEC via federated multi-agent reinforcement learning and potential fields has closed oa status in the ScholarIQ index.

What is the DOI of Joint trajectory and offloading optimization in UAV-assisted MEC via federated multi-agent reinforcement learning and potential fields?

ScholarIQdoi

The DOI for Joint trajectory and offloading optimization in UAV-assisted MEC via federated multi-agent reinforcement learning and potential fields is on the source record.

What is the OpenAlex record for Joint trajectory and offloading optimization in UAV-assisted MEC via federated multi-agent reinforcement learning and potential fields?

ScholarIQopenalex

The OpenAlex for Joint trajectory and offloading optimization in UAV-assisted MEC via federated multi-agent reinforcement learning and potential fields is on the source record.

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