•DSS aid in problem solving by allowing for manipulation of data & models whereas ES allow experts to 'teach' computers about their field so that the system may support more of the decision making process for less expert decision makers. • DSS most often contain equations that the system uses to solve problems or update reports immediately, and the users makes the final decisions on the basis of the information whereas an expert system works from a much larger set of modeling rules,uses concepts from AI to process and store the knowledge base & scans base to suggest a final decision decision through inference. •DSS only supports the decision making process & a human user is required to weigh all the factors in making a decision whereas ES must acquire knowledge from an expert and apply a large but standard set of probability based rules to make a decision in a specific problem setting.
Chat with our AI personalities
•DSS aid in problem solving by allowing for manipulation of data & models whereas ES allow experts to 'teach' computers about their field so that the system may support more of the decision making process for less expert decision makers. • DSS most often contain equations that the system uses to solve problems or update reports immediately, and the users makes the final decisions on the basis of the information whereas an expert system works from a much larger set of modeling rules,uses concepts from AI to process and store the knowledge base & scans base to suggest a final decision decision through inference. •DSS only supports the decision making process & a human user is required to weigh all the factors in making a decision whereas ES must acquire knowledge from an expert and apply a large but standard set of probability based rules to make a decision in a specific problem setting.
Answer 1.
Human Experts
Expert Systems
Answer 2.
The difference is that human understands the variability in ambiquity and uncertainty in the open world while the expert system has to go through repeated induction and reduction of rules in its closed world view which is constraint bounded by its limited knowledge capacity to reason. An, expert system is not always learning and growing on its own but needs a human to guide its very learning of a domain and to be able to reason on facts that it already knows. But, a human is always learning and adapting to changes in the environment even facts that it does not necessarily knows already but is able to reason on them without having to rely on someones guidance as it gets older at least for the basics. In fact, a human also naturally knows where to seek guidance and where to source for more information and then to reason on things from past knowledge that it is able to retain for future. A human mind is like a massive neural network. So comparison is really between a Human Neural Network vs an expert system. Even an artificial neural network is only a very small model of the capacity of the human mind.
Conventional programming creates solutions to help different professionals in their fields. Expert systems, on the other hand, produce solutions that replace the human professional in the field.
Read more: Difference Between GDSS and DSS | Difference Between | GDSS vs DSS http://www.differencebetween.net/business/structure-systems/difference-between-gdss-and-dss/#ixzz2BlH9CFoj
Expert systems are computerized tools designed to enhance the quality and availability of knowledge required by decision makers in a wide range of industries. They augment conventional programs such as databases, word processors, and spreadsheet analysis.
Expert systems differ from conventional applications software in the following ways:
o The expert system shell, or interpreter.
o The existence of a "knowledge base," or system of related concepts that enable the computer to approximate human judgment.
o The sophistication of the user interface.
While any conventional programming language can be used to build a knowledge base, the expert system shell simplifies the process of creating a knowledge base. It is the shell that actually processes the information entered by a user; relates it to the concepts contained in the knowledge base; and provides an assessment or solution for a particular problem.
The main purpose of the knowledge base is to provide the guts of the expert system--the connections between ideas, concepts, and statistical probabilities that allow the reasoning part of the system to perform an accurate evaluation of a potential problem. Knowledge bases are traditionally described as large systems of "if then" statements, but this description is misleading because knowledge bases may not contain definitive rules at all, but may contain only associative relationships among different concepts, statistical information about the probability of certain solutions, or simply large databases of facts that can be compared to one another based on simple conventions intrinsic to the expert system.
both of them are the same
HUMAN EXPERT-skills and knowledge an deterriote overtime.training human expert is an expensive and lengthy process that may not even gurantee good results.susceptible to emotional and psychological factors that can impair decision making.scare and typically high demand salaries. EXPERT SYSTEM-provides permanent skills and knowledge.artificial expertise from system is easily reproduced and transferred,simply by duplicating the computer program.provides consistent are reproducible results.expert system are reffered cheap to operate and maintain.
there is none........
Devices do not care with this difference. Humans do.
A robot is a physical machine capable of performing tasks autonomously or semi-autonomously, often with sensors and actuators for interacting with its environment. An expert system, on the other hand, is a software program that uses artificial intelligence techniques to mimic the decision-making abilities of a human expert in a specific domain. While a robot can physically interact with the world, an expert system is purely software-based and relies on rules and knowledge bases to make decisions.
This difference could be succinctly described as those things that human beings didn't make (the environment) and those things that human beings did make (technology).