Generative Task Network:New Paradigm for Autonomic Task Planning and Execution Based on LLM

Owing to the development of generative artificial intelligence,the intelligent planning technology of unmanned systems is set to undergo a new transformation.This paper first analyzes the shortcomings of traditional intelligent task planning paradigms in terms of generalization,transferability and coherence.In response,it proposes a new paradigm for task planning and execution based on large language models,namely generative task network.This method enables unmanned systems to autonomously discover tasks,intelligently plan,and automatically execute them,forming a closed-loop from problem to solution.It also endows the task planning process of unmanned systems with the advantages of generalization and ease of transfer.This paper then introduces the concept of the generative task network,defines its key elements and models its process,and subsequently designs a ge-neral application architecture.Finally,an application analysis is conducted taking the aviation materials warehouse of N Airlines as the scenario,effectively enhancing the intelligence and automation levels of unmanned systems in warehouse management.

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Publication Details

Journal
SHILAP Revista de lepidopterología
Published
2025-03-01
DOI
https://doi.org/10.11896/jsjkx.241100068
Primary Topic
Real-Time Systems Scheduling
Type
article
Field-Weighted Citation Impact
0.00
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article

Generative Task Network:New Paradigm for Autonomic Task Planning and Execution Based on LLM

SHILAP Revista de lepidopterología
Real-Time Systems Scheduling
article

Generative Task Network:New Paradigm for Autonomic Task Planning and Execution Based on LLM

article en

Abstract

Owing to the development of generative artificial intelligence,the intelligent planning technology of unmanned systems is set to undergo a new transformation.This paper first analyzes the shortcomings of traditional intelligent task planning paradigms in terms of generalization,transferability and coherence.In response,it proposes a new paradigm for task planning and execution based on large language models,namely generative task network.This method enables unmanned systems to autonomously discover tasks,intelligently plan,and automatically execute them,forming a closed-loop from problem to solution.It also endows the task planning process of unmanned systems with the advantages of generalization and ease of transfer.This paper then introduces the concept of the generative task network,defines its key elements and models its process,and subsequently designs a ge-neral application architecture.Finally,an application analysis is conducted taking the aviation materials warehouse of N Airlines as the scenario,effectively enhancing the intelligence and automation levels of unmanned systems in warehouse management.

SHILAP Revista de lepidopterología
National University of Defense Technology (CN)
Openalex Percentile: Top 43%
Real-Time Systems Scheduling
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