Scenario-Driven Evaluation of Autonomous Agents: Integrating Large Language Model for UAV Mission Reliability

Drones, Год журнала: 2025, Номер 9(3), С. 213 - 213

Опубликована: Март 17, 2025

The Internet of Drones (IoD) integrates autonomous aerial platforms with security, logistics, agriculture, and disaster relief. Decision-making in IoD suffers real-time adaptability, platform interoperability, scalability. Conventional decision frameworks heuristic algorithms narrow Artificial Intelligence (AI) falter complex environments. To mitigate these, this study, an augmented model is proposed, combining large language models (LLMs) retrieval-augmented generation (RAG) for enhancing intelligence. Centralized intelligence achieved by processing environment factors, mission logs, telemetry, adaptability. Efficient retrieval contextual information through RAG merged LLMs timely, correct decision-making. Contextualized decision-making vastly improves adaptability uncertain environments a drone network. With RAG, the introduces scalable, adaptable operations solution. It enables development industries, future work computational efficiency, ethics, extending operational In-depth analysis collection telemetry logs factors was conducted. Decision accuracy, response time, relevance were measured to gauge system effectiveness. model’s performance increased remarkably, BLEU 0.82 cosine similarity 0.87, proving its effectiveness commands. latency averaged 120 milliseconds, suitability use cases.

Язык: Английский

Chaotic behavior of a new fractional-order financial system and its predefined-time sliding mode control based on the RBF neural network

Electronic Research Archive, Год журнала: 2025, Номер 33(5), С. 2762 - 2799

Опубликована: Янв. 1, 2025

Язык: Английский