How does symbolic logic work?

Symbolic logic involves breaking down problems and reasoning symbolically, often regarded as a compact representation that helps understand abstract concepts. Jordan Fisher discusses the intuition behind this: our brains, when working on abstract tasks, tend to engage in symbolic reasoning. This process could be visualized as thinking through the graph structure of a problem, exploring its various branches or sub-problems, and analyzing them. He believes that merging symbolic logic with advanced models in computing could significantly advance problem-solving capabilities 1.

Furthermore, symbolic logic's application in artificial intelligence highlights the importance of creating understandable, compact representations of concepts. For instance, in machine learning, there is a significant emphasis on making systems produce explanations that are not just effective but symbolically interpretable. This helps in expanding human vocabulary and understanding by transforming complex automated reasoning into human-understandable concepts for collaboration and enhanced interpretability 2.