ACTA AERONAUTICAET ASTRONAUTICA SINICA >
An explainable decision-making method for resource allocation in IMA system based on PPO-SHAP
Received date: 2025-02-13
Revised date: 2025-04-01
Accepted date: 2024-06-26
Online published: 2025-07-15
Supported by
Ministerial-level Project
With the development of aviation Artificial Intelligence （AI） technology， the intelligent application software residing on the Integrated Modular Avionics （IMA） platform faces challenges such as resource scarcity and unreliable decision-making. Firstly， based on the consideration of avionics system architectural elements， the optimisation objective of IMA resource allocation decision-making under multiple constraints is designed. The proximal policy optimization algorithm is used to solve the near-optimal allocation scheme of IMA resources in the sequential decision-making process. Next， a decision attribution explanation framework for IMA resource allocation is established， and the expert policy of the reinforcement learning agent is extracted by aggregating and resampling the training dataset. Then， the SHapley Additive exPlanations （SHAP） method is used to achieve a combined global and local explanation of IMA resource allocation decisions. Simulation experiments and result analysis show that， compared with the greedy algorithm and other policy-based reinforcement learning algorithms， the proposed method exhibits good convergence speed and learning effect， and is remarkably superior in solving the IMA resource allocation problem. Additionally， this method generates quantitative and visual feature attribution explanations， which reveals the impact of input features on decision-making and clarify decision intent， thereby providing methodological guidance for airworthiness compliance validation of AI-based avionics system in terms of explainability.
Jiachen LIU , Lei DONG , Zijing SUN , Ye NI , Xi CHEN , Peng WANG . An explainable decision-making method for resource allocation in IMA system based on PPO-SHAP[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2025 , 46(24) : 331872 -331872 . DOI: 10.7527/S1000-6893.2025.31872
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