Hybrid AI Architectures for Complex Decision Support Systems
This paper analyzes hybrid AI systems that combine symbolic approaches (rule-based reasoning, interpretability) with sub-symbolic methods (machine learning, neural networks) to improve flexibility and robustness and suggests future directions, including explainable AI and scalable distributed architectures.