Month: April 2022

What is an Expert System?

An expert system is a computer program that is designed to solve complex problems and to provide decision-making ability like a human expert. It performs this by extracting knowledge from its knowledge base using the reasoning and inference rules according to the user queries. The expert system is a part of AI, and the first… Continue reading What is an Expert System?

Bayesian Belief Network in AI

Bayesian belief network is key computer technology for dealing with probabilistic events and to solve a problem which has uncertainty. We can define a Bayesian network as: “A Bayesian network is a probabilistic graphical model which represents a set of variables and their conditional dependencies using a directed acyclic graph.” It is also called a Bayes… Continue reading Bayesian Belief Network in AI

Bayes theorem in Artificial intelligence

Bayes’ theorem: Bayes’ theorem is also known as Bayes’ rule, Bayes’ law, or Bayesian reasoning, which determines the probability of an event with uncertain knowledge. In probability theory, it relates the conditional probability and marginal probabilities of two random events. Bayes’ theorem was named after the British mathematician Thomas Bayes. The Bayesian inference is an application of Bayes’ theorem, which… Continue reading Bayes theorem in Artificial intelligence

Inductive vs Deductive reasoning

Reasoning in artificial intelligence has two important forms, Inductive reasoning, and Deductive reasoning. Both reasoning forms have premises and conclusions, but both reasoning are contradictory to each other. Following is a list for comparison between inductive and deductive reasoning: Deductive reasoning uses available facts, information, or knowledge to deduce a valid conclusion, whereas inductive reasoning… Continue reading Inductive vs Deductive reasoning

Reasoning in Artificial intelligence

In previous topics, we have learned various ways of knowledge representation in artificial intelligence. Now we will learn the various ways to reason on this knowledge using different logical schemes. Reasoning: The reasoning is the mental process of deriving logical conclusion and making predictions from available knowledge, facts, and beliefs. Or we can say, “Reasoning… Continue reading Reasoning in Artificial intelligence

Difference b/w backward chaining and forward chaining

Following is the difference between the forward chaining and backward chaining: Forward chaining as the name suggests, start from the known facts and move forward by applying inference rules to extract more data, and it continues until it reaches to the goal, whereas backward chaining starts from the goal, move backward by using inference rules… Continue reading Difference b/w backward chaining and forward chaining

Forward Chaining and backward chaining in AI

In artificial intelligence, forward and backward chaining is one of the important topics, but before understanding forward and backward chaining lets first understand that from where these two terms came. Inference engine: The inference engine is the component of the intelligent system in artificial intelligence, which applies logical rules to the knowledge base to infer… Continue reading Forward Chaining and backward chaining in AI