Expert systems and Artificial Intelligence (AI) play a crucial role in decision support systems (DSS) by enhancing data analysis and providing intelligent recommendations. Expert systems utilize knowledge from human experts to solve specific problems, enabling users to make informed decisions based on established rules and heuristics. AI, particularly through machine learning and data mining, can analyze vast datasets, identify patterns, and predict outcomes, thereby improving the accuracy and efficiency of decision-making processes. Together, they empower organizations to make data-driven decisions, optimize resources, and respond dynamically to changing conditions.
An artificial intelligence knowledge base aims to compile human expert knowledge to aid in decision-making, problem-solving, and other processes. Knowledge base systems have been created over time to support a variety of organisational processes.
Different tasks in engineering problem solving require different computation tools. Artificial intelligence techniques, as a tool, provide the capability to the program to solve complex problems by extracting ideas from data of a knowledge-base usually a database using a domain oriented set of rules in a manner that a human brain archives decision-making process to come up with a comprehensible solution. Expert systems are profession specialized programs. They are artificial intelligent systems but are inclined to only one area of professionalism. Artificial intelligence unlike conventional programs which concentrate on what data to analyze to come up with a solution, they concentrate on how an expert makes choices when faced with a professional challenge and why he/she makes such choices. These abilities are only provided by Artificial intelligence techniques and this is a role they play in decision support functions. Hope you find the answer enlighting. (Jones Kafwilo [jkafwilo@yahoo.com])
Certified Artificial Intelligence (AI) Expert certification is a thoughtfully designed learning program for new enthusiasts in data science and AI fields.
The component that delivers expert advice is typically referred to as a knowledge base or an advisory system. This can include artificial intelligence algorithms, decision support systems, or expert systems that analyze data and provide recommendations based on established criteria and expert input. In many cases, these systems are designed to enhance human decision-making by synthesizing vast amounts of information into actionable insights.
Samuel Holtzman has written: 'Intelligent decision systems' -- subject(s): Artificial intelligence, Data processing, Decision making, Expert systems (Computer science), Medicine
fuzzy expert system used to handle uncertainties.
Daniel Edmund O'Leary has written: 'Expert systems and artificial intelligence in internal auditing' -- subject(s): Artificial intelligence, Auditing, Auditing, Internal, Data processing, Expert systems (Computer science), Internal Auditing
Generative Artificial Intelligence (AI) represents the cutting edge of technological innovation, seamlessly blending creativity and intelligence.
The term "expert system" refers to an artificial intelligence. An expert system is a program that has the ability to answer questions by taking knowledge on a subject and converting it to codes.
An Inference Engine in Artificial Intelligence is a core component that applies logical rules to a knowledge base to derive new information or make decisions. It processes input data and uses reasoning techniques, such as forward or backward chaining, to infer conclusions or solutions based on the available facts. Inference engines are commonly used in expert systems, decision support systems, and various AI applications to automate reasoning and problem-solving.
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N. P. Padhy has written: 'Artificial intelligence and intelligent systems' -- subject(s): Artificial intelligence, Expert systems (Computer science), Intelligent agents (Computer software)