👉 Wagner computing, developed by David Wagner, is a computational paradigm that focuses on the integration of human and machine intelligence to solve complex problems more effectively than either can alone. It emphasizes the use of cognitive architectures, which are models that simulate human thought processes, to bridge the gap between human intuition and machine precision. This approach leverages techniques such as probabilistic reasoning, symbolic manipulation, and machine learning to create systems that can understand context, reason abstractly, and learn from data, ultimately enhancing decision-making in domains like healthcare, finance, and autonomous systems. By combining these elements, Wagner computing aims to create more adaptive, intelligent, and human-like AI systems that can operate in dynamic and uncertain environments.
