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Addressing environmental stochasticity in reconfigurable intelligent surface aided unmanned aerial vehicle networks: Multi-task deep reinforcement learning based optimization for physical layer security
Research article (Internet of Things, 2024) · cited 10× · AI/ML
Addressing environmental stochasticity in reconfigurable intelligent surface aided unmanned aerial vehicle networks: Multi-task deep reinforcement learning based optimization for physical layer security
Summary
Addressing environmental stochasticity in reconfigurable intelligent surface aided unmanned aerial vehicle networks: Multi-task deep reinforcement learning based optimization for physical layer security is a scholarly article[1].
Key Facts
Addressing environmental stochasticity in reconfigurable intelligent surface aided unmanned aerial vehicle networks: Multi-task deep reinforcement learning based optimization for physical layer security's instance of is recorded as scholarly article[2].
References
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Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.
APA4ort.xyz Knowledge Graph. (2026). Addressing environmental stochasticity in reconfigurable intelligent surface aided unmanned aerial vehicle networks: Multi-task deep reinforcement learning based optimization for physical layer security. Retrieved May 24, 2026, from https://4ort.xyz/entity/addressing-environmental-stochasticity-in-reconfigurable-intelligent-surface-aided-unmanned-aerial-vehicle-networks-mult
MLA“Addressing environmental stochasticity in reconfigurable intelligent surface aided unmanned aerial vehicle networks: Multi-task deep reinforcement learning based optimization for physical layer security.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/addressing-environmental-stochasticity-in-reconfigurable-intelligent-surface-aided-unmanned-aerial-vehicle-networks-mult.
BibTeX@misc{4ortxyz_addressing-environmental-stochasticity-in-reconfigurable-intelligent-surface-aided-unmanned-aerial-vehicle-networks-mult_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Addressing environmental stochasticity in reconfigurable intelligent surface aided unmanned aerial vehicle networks: Multi-task deep reinforcement learning based optimization for physical layer security}}, year = {2026}, url = {https://4ort.xyz/entity/addressing-environmental-stochasticity-in-reconfigurable-intelligent-surface-aided-unmanned-aerial-vehicle-networks-mult}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Addressing environmental stochasticity in reconfigurable intelligent surface aided unmanned aerial vehicle networks: Multi-task deep reinforcement learning based optimization for physical layer security — https://4ort.xyz/entity/addressing-environmental-stochasticity-in-reconfigurable-intelligent-surface-aided-unmanned-aerial-vehicle-networks-mult (retrieved 2026-05-24)
