1.
Rules used in automated decision systems (ADS) can be derived based on experience
Correct Answer
A. True
Explanation
Automated decision systems (ADS) can derive rules based on experience because they can analyze large amounts of data and learn patterns and correlations from it. By processing and analyzing past experiences, ADS can identify trends and make decisions based on that knowledge. This allows the system to improve its decision-making capabilities over time and make more accurate predictions or recommendations. Therefore, it is true that rules used in automated decision systems can be derived based on experience.
2.
Most business decision rules are the same across industries
Correct Answer
B. False
Explanation
The statement "Most business decision rules are the same across industries" is false. Business decision rules can vary greatly across industries due to differences in market conditions, customer preferences, regulatory requirements, and competitive landscapes. Each industry has its own unique set of challenges and opportunities, which necessitate tailored decision-making approaches. For example, decision rules in the healthcare industry may prioritize patient safety and regulatory compliance, while decision rules in the technology industry may focus on innovation and speed to market. Therefore, it is important for businesses to adapt their decision rules to the specific characteristics of their industry.
3.
Flight pricing systems are examples of semi-automated decision systems that require managerial input for each decision.
Correct Answer
B. False
Explanation
Flight pricing systems are not examples of semi-automated decision systems that require managerial input for each decision. These systems are typically fully automated and use algorithms to determine the prices based on various factors such as demand, competition, and costs. The pricing decisions are made by the system itself without the need for constant managerial input. Therefore, the correct answer is False.
4.
A revenue management (RM) system for an airline seeks to minimize each customer's ticket price of travel on the airline's flights.
Correct Answer
B. False
Explanation
A revenue management (RM) system for an airline does not seek to minimize each customer's ticket price of travel on the airline's flights. Instead, the primary goal of an RM system is to optimize the revenue generated by selling tickets by considering factors such as demand, pricing strategies, and inventory management. The system aims to maximize overall revenue rather than minimizing individual ticket prices. Therefore, the statement is false.
5.
Rule-based systems have their roots in artificial intelligence.
Correct Answer
A. True
Explanation
Rule-based systems are a type of artificial intelligence system that uses a set of predefined rules to make decisions or solve problems. These systems rely on logical reasoning and inference to process information and make decisions. Therefore, it can be concluded that rule-based systems have their roots in artificial intelligence.
6.
Expert systems (ES) are computer-based information systems that use expert knowledge to attain high-leveldecision performance in a narrowly defined problem domain
Correct Answer
A. True
Explanation
Expert systems are computer-based information systems that use expert knowledge to attain high-level decision performance in a narrowly defined problem domain. This means that they are designed to mimic the decision-making abilities of human experts in a specific field. By utilizing this expert knowledge, expert systems can provide accurate and reliable solutions to problems within their defined domain. Therefore, the statement "Expert systems (ES) are computer-based information systems that use expert knowledge to attain high-level decision performance in a narrowly defined problem domain" is true.
7.
A person's decision performance and level of knowledge are typical criteria that determine their level of expertise in a particular subject
Correct Answer
A. True
Explanation
The statement is true because a person's decision performance and level of knowledge are important factors in determining their expertise in a particular subject. Expertise is typically measured by how well someone can make informed decisions and solve problems related to a specific field. A person who consistently demonstrates good decision-making skills and possesses a high level of knowledge in a subject can be considered an expert in that area.
8.
The basic rationale of artificial intelligence is to use mathematical calculation rather than symbolicreasoning.
Correct Answer
B. False
Explanation
The explanation for the given correct answer, which is "False," is that the basic rationale of artificial intelligence is not to use mathematical calculation instead of symbolic reasoning. In fact, artificial intelligence combines both mathematical calculations and symbolic reasoning to mimic human intelligence and solve complex problems. Mathematical calculations are used for tasks such as data analysis and pattern recognition, while symbolic reasoning is employed for tasks that require logical reasoning and decision-making. Therefore, the statement in the question is incorrect.
9.
While most first-generation Expert Systems (ES) use if-then rules to represent and store their knowledge, second-generation ES are more flexible in adopting multiple knowledge representation and reasoning methods
Correct Answer
A. True
Explanation
The statement is true because first-generation Expert Systems (ES) primarily rely on if-then rules to represent and store their knowledge. However, second-generation ES are more advanced and can utilize multiple knowledge representation and reasoning methods, making them more flexible in their approach.
10.
A nonexpert uses the development environment of an expert system to obtain advice and to solveproblems using the expert knowledge embedded into the system
Correct Answer
B. False
Explanation
A nonexpert does not use the development environment of an expert system to obtain advice and solve problems. The development environment is typically used by experts to design, develop, and test the expert system. Nonexperts, on the other hand, use the deployed or operational version of the expert system to access the expert knowledge and obtain advice for problem-solving purposes. Therefore, the statement is false.
11.
Knowledge acquisition from experts is a complex task that requires specialized expertise to conductsuccessfully.
Correct Answer
A. True
Explanation
Knowledge acquisition from experts is indeed a complex task as it involves gathering information and expertise from individuals who have specialized knowledge in a particular field. Conducting this task successfully requires not only the ability to effectively communicate and extract information from experts but also the understanding and expertise to interpret and synthesize the acquired knowledge. Therefore, the statement that knowledge acquisition from experts requires specialized expertise to conduct successfully is true.
12.
The knowledge base in an expert system must correspond exactly to the format of the knowledge base in the organization where it will be utilized
Correct Answer
B. False
Explanation
The statement is false because the knowledge base in an expert system does not have to correspond exactly to the format of the knowledge base in the organization where it will be utilized. Expert systems are designed to capture and represent knowledge in a structured and organized manner, which may differ from the organization's existing knowledge base format. The purpose of an expert system is to provide accurate and efficient problem-solving capabilities, not to replicate the organization's knowledge base format.
13.
The inference engine, also known as the control structure or the rule interpreter (in rule-based ES), is essentially a computer program that provides a methodology for reasoning about information in the knowledge base and on the blackboard to formulate appropriate conclusions
Correct Answer
A. True
Explanation
The explanation for the given correct answer is that the inference engine is indeed a computer program that allows for reasoning about information in the knowledge base and on the blackboard. It helps in formulating appropriate conclusions based on the available information. Therefore, the statement is true.
14.
The critical component of a knowledge refinement system is the self-learning mechanism that allows it to adjust its knowledge base and its processing of knowledge based on the evaluation of its recent past performances.
Correct Answer
A. True
Explanation
The explanation for the correct answer is that a knowledge refinement system relies on a self-learning mechanism to improve its knowledge base and processing of knowledge. This mechanism allows the system to evaluate its recent past performances and make adjustments accordingly. By continuously learning from its experiences, the system can refine its knowledge and improve its performance over time. Therefore, the statement is true.
15.
Validation of knowledge is usually done by a human expert in the knowledge domain
Correct Answer
A. True
Explanation
Validation of knowledge is usually done by a human expert in the knowledge domain because human experts possess the necessary expertise, experience, and understanding of the subject matter to accurately assess and verify the correctness and reliability of the knowledge. They can critically evaluate the information, apply their judgment and reasoning skills, and ensure that the knowledge aligns with established standards and principles in the domain. Human experts are able to bring their contextual understanding and intuition to the validation process, making them invaluable in ensuring the accuracy and quality of knowledge in their respective fields.
16.
Once validated, the knowledge acquired from experts or induced from a set of data must be represented in a format that does not need to be understandable by humans but must be executable on computers.
Correct Answer
B. False
Explanation
The statement suggests that the knowledge acquired from experts or data needs to be represented in a format that can be executed by computers, but it does not need to be understandable by humans. The correct answer is False because the knowledge representation should ideally be understandable by humans as well, in order to ensure transparency, interpretability, and effective communication between humans and machines.
17.
Inference rules and knowledge rules are both used to solve problems in a rule-based expert system
Correct Answer
B. False
Explanation
Inference rules and knowledge rules are not both used to solve problems in a rule-based expert system. Inference rules are used to draw conclusions or make inferences based on the given information or knowledge. On the other hand, knowledge rules are used to represent the domain-specific knowledge or expertise that the expert system possesses. While both types of rules are important in a rule-based expert system, they serve different purposes in the problem-solving process.
18.
Unlike human experts, expert systems do not need to explain their views, recommendations, or decisions
Correct Answer
B. False
Explanation
Expert systems, like any other decision-making system, should ideally be able to explain their views, recommendations, or decisions. Transparency and interpretability are crucial for users to understand and trust the system's output. By providing explanations, expert systems can enhance their credibility and allow users to validate and understand the reasoning behind their outputs. Therefore, the statement that expert systems do not need to explain their views, recommendations, or decisions is false.
19.
Who are automated decision systems (ADS) primarily designed for?
Correct Answer
A. Frontline workers who must make decisions rapidly
Explanation
Automated decision systems (ADS) are primarily designed for frontline workers who must make decisions rapidly. These workers often face time-sensitive situations where quick decision-making is crucial. ADS can assist them by providing real-time data, analysis, and recommendations, enabling them to make informed decisions quickly and efficiently. This technology helps streamline processes and improves the overall productivity of frontline workers, ensuring that they can handle their responsibilities effectively.
20.
Revenue management systems modify the prices of products and services dynamically based on
Correct Answer
B. Business rules, demand, and supply.
Explanation
Revenue management systems modify the prices of products and services dynamically based on business rules, demand, and supply. Business rules refer to the specific guidelines and strategies set by the company to optimize revenue. Demand is a crucial factor as it determines the level of customer interest and willingness to pay for the products or services. Supply also plays a role as it affects the availability and cost of resources needed to deliver the products or services. By considering these factors, revenue management systems can adjust prices in real-time to maximize profitability.
21.
What does self-knowledge in an expert system (ES) mean?
Correct Answer
B. The ES "knows" that it exists.
Explanation
Self-knowledge in an expert system refers to the system's awareness of its own existence. This means that the ES has the ability to recognize itself as a separate entity and understand its own existence as an intelligent system. It implies that the ES has a level of consciousness and self-awareness, similar to how humans possess self-knowledge. This understanding of its own existence allows the ES to effectively analyze and interpret information, make decisions, and provide explanations for its conclusions.
22.
How does an expert system differ from conventional systems?
Correct Answer
A. Expert systems handle qualitative data easily.
Explanation
Expert systems differ from conventional systems because they are capable of handling qualitative data easily. Unlike conventional systems, which primarily deal with quantitative data, expert systems have the ability to process and interpret qualitative information. This allows them to analyze and make decisions based on subjective or non-numeric data, such as expert opinions or descriptions. This feature makes expert systems particularly useful in domains where qualitative knowledge and expertise are crucial, such as medical diagnosis or legal decision-making.
23.
The MYCIN Expert System was used to diagnose bacterial infections using
Correct Answer
A. A set of 500 rules on the subject.
Explanation
The MYCIN Expert System was used to diagnose bacterial infections using a set of 500 rules on the subject. These rules were programmed into the system to mimic the decision-making process of human experts in diagnosing infections. The system would analyze the symptoms and medical data provided by the user and apply these rules to determine the most likely diagnosis. Each rule represented a specific condition or characteristic associated with different types of infections, allowing the system to provide accurate and efficient diagnoses.
24.
Which module is missing from most expert systems?
Correct Answer
C. Knowledge refinement subsystem
Explanation
Expert systems are designed to mimic human expertise in a specific domain. They consist of several modules that work together to provide intelligent decision-making capabilities. The inference engine is responsible for reasoning and making inferences based on the knowledge stored in the knowledge base subsystem. The user interface subsystem enables interaction between the user and the expert system. The knowledge base subsystem stores the domain-specific knowledge. However, the knowledge refinement subsystem is not a standard module in most expert systems. It is not necessary for the functioning of the system as it focuses on improving the knowledge base over time, rather than being an essential component for decision-making.
25.
All the following statements about how an expert system operates are true EXCEPT
Correct Answer
C. Inference engines contain an explanation subcomponent.
Explanation
An expert system operates by incorporating knowledge from human experts, which is stored in a knowledge base. A knowledge engineer creates inferencing rules that allow the system to make logical deductions and draw conclusions. Inference engines are responsible for executing these rules and generating results. However, the statement that inference engines contain an explanation subcomponent is not true. Explanation subcomponents are typically found in the user interface or separate modules of an expert system, not within the inference engine itself.
26.
Which of the following is NOT a stage of knowledge engineering?
Correct Answer
C. Knowledge consolidation
Explanation
Knowledge consolidation is not a stage of knowledge engineering. Knowledge engineering involves the processes of knowledge representation, knowledge acquisition, and knowledge validation. Knowledge consolidation refers to the process of integrating and organizing existing knowledge, but it is not considered a distinct stage in the knowledge engineering process.
27.
It is difficult to acquire knowledge from experts for all the following reasons EXCEPT
Correct Answer
B. many business areas have no identifiable experts.
Explanation
The given answer states that "many business areas have no identifiable experts" is not a reason why it is difficult to acquire knowledge from experts. This implies that there are identifiable experts available in many business areas, which contradicts the other reasons mentioned. The other reasons listed in the question, such as experts changing their behavior when observed, the complexity of testing and refining knowledge, and experts not being able to articulate their work, all contribute to the difficulty in acquiring knowledge from experts.
28.
Using certainty factors, a rule declares that IF competition is strong, CF = 70 AND margins are above 15% CF = 100 THEN sales demand will decline. If both conditions are true, what is the CF of the conclusion?
Correct Answer
C. 70%
Explanation
The conclusion states that "sales demand will decline" if both conditions are true. The first condition has a certainty factor (CF) of 70% and the second condition has a CF of 100%. According to the rules of certainty factors, the CF of the conclusion is determined by taking the minimum CF of the two conditions, which in this case is 70%. Therefore, the CF of the conclusion is 70%.
29.
Using certainty factors, a rule declares that IF competition is strong, CF = 70 OR margins are above 15% CF= 100 THEN sales demand will decline. If both conditions are true, what is the CF of the conclusion?
Correct Answer
D. 100%
Explanation
The certainty factor (CF) of the conclusion is 100% because both conditions in the rule are true. The rule states that IF competition is strong (CF = 70) OR margins are above 15% (CF = 100), THEN sales demand will decline. Since both conditions are true, the CF of the conclusion is the highest CF value mentioned in the rule, which is 100%.
30.
Which category of expert systems that includes weather forecasting and economic/financial forecasting?
Correct Answer
C. Prediction ES
Explanation
Prediction expert systems are designed to make forecasts and predictions based on available data and knowledge. They use algorithms and models to analyze historical data and make predictions about future events or outcomes. Weather forecasting and economic/financial forecasting are examples of prediction expert systems as they use data and knowledge to predict future weather patterns or economic trends. These systems help in making informed decisions and planning strategies based on the predicted outcomes.
31.
Which tool would be best to use when there is a need to very rapidly and cheaply develop a rule-based expert system?
Correct Answer
C. AN ES shell
Explanation
An ES shell would be the best tool to use when there is a need to rapidly and cheaply develop a rule-based expert system. ES shells are specifically designed to facilitate the development of expert systems by providing a user-friendly interface, pre-built knowledge representation and inference mechanisms, and other helpful features. This allows developers to quickly create and test rule-based expert systems without the need for extensive programming or knowledge in specialized languages like LISP or Prolog. The other options, ASP.NET and C++, are general-purpose programming languages and may not offer the same level of efficiency and ease of use for developing expert systems.