Explain the techniques used to handle uncertainty and incomplete information within expert systems.

Expert systems often encounter uncertainty and incomplete information, which can affect the accuracy and reliability of their decision-making. To address these challenges, several techniques are used to handle uncertainty and incomplete information within expert systems. Here are some of the commonly employed techniques: 1. Fuzzy Logic: * Fuzzy logic is a mathematical framework that deals with uncertainty by allowing degrees of truth rather than strict binary values. * It allows for the representation and manipulation of vague or imprecise information by assigning membership degrees to linguistic variables. * Fuzzy logic enables expert systems to handle uncertain or ambiguous inputs and make decisions based on fuzzy rules and fuzzy inference. 2. Probabilistic Reasoning: * Probabilistic reasoning techniques, such as Bayesian networks, are used to model and reason under uncertainty. * These techniques involve assigning probabilities to different events or states and updating those probabilities based on new evidence or observations. * By incorporating probabilistic reasoning, expert systems....