Logic and Expert Systems

Human intelligence relies heavily on reasoning, solving problems, and understanding complex patterns through logic. A key challenge emerges as we strive to create intelligent systems: How can we enable computers to grasp logic in a way that mirrors human thinking? How do we represent knowledge, allowing machines to process, represent, and manipulate data meaningfully? Just as humans use logic to draw conclusions and solve problems, computers rely on formal logic systems to interpret information and execute tasks. Let's explore different types of logic that are used to structure knowledge and enable intelligent behavior in AI systems.

Propositional logic

Imagine you want a computer to understand that it is raining today. How would you convey this information in a way the computer can process, given that it only understands true or false values? 

Logic is the study of principles of valid inference and reasoning. It provides a formal language for representing information and a set of rules for manipulating it. A statement that could be true or false is called a proposition, e.g., it is raining today. We can represent this statement with $p$. What if we want to say that ...