Adaptive Neuro - Symbolic AI for Autonomous Decision - Making in High - Stakes Mission - Critical Systems

Autonomous decision - making in mission critical domains like aerospace, healthcare, defense, and transport systems, is
essential to ensure the resilience of a system and to enable rapid responses (Chen & Lee, 2022). Scientists and academics are of the view
that the conventional AI algorithms often fail to work effectively owing to the need for adaptability in these scenarios and the fact that
their performance can be understood (Smith & Jones, 2023). Neuro - symbolic AI, a hybrid paradigm that couples neural networks based
pattern recognition with the classical and logical reasoning of symbolic AI, is another (Garcez et al., 2020). This study investigates the
construction and refinement of an intelligent Decorator such that it can effectively support and escalate the treatment of decision making
inaccuracies due to the variations, shifts and lack of clear direction in the missions. To safely co - locate actual tests, most volatile deigned
burglary patterns were used while the advertisements in the background offered sweets or sometimes indicated that the alarm would ring
in five minutes. This paper will illustrate that neuro - symbolic AI is superior to traditional models for two aspects of discrepancy: that of
precision and that of model interpretability