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

Deepak Kaul

Abstract: 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.

Keywords: Autonomous decision - making, neuro - symbolic AI, adaptability, mission critical systems, AI algorithms