Artificial Intelligence - Expert Systems

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BCIS 1305 BUSINESS COMPUTER APPLICATIONS

Homework 5



Part I

True/False



1. The intelligence phase of decision making finds or recognizes a problem,

need, or opportunity.



a) True b) False





2. The choice phase of decision making considers ways to solve problems, fill

needs, or take advantage of opportunities.



a) True b) False





3. A structured decision involves processing a certain kind of information in a

specified way so that you will always get the right answer. No "feel" or

intuition is necessary.



a) True b) False





4. A recurring decision is one that happens repeatedly, and often periodically,

whether weekly, monthly, quarterly, or yearly.



a) True b) False





5. Most decisions fall somewhere between structured and nonstructured.



a) True b) False





6. A decision support system (DSS) is a highly flexible and interactive IT

system that is designed to support decision making when the problem is not

structured.



a) True b) False





7. Artificial intelligence (AI) is the science of making humans imitate

computer thinking and behavior.



a) True b) False





8. Expert systems are adaptive systems that work independently, carrying out

specific, repetitive, or predicable tasks.



a) True b) False





9. An expert system is also called a knowledge-based system.



a) True b) False





10. An expert system is fundamentally the same as a DSS.



a) True b) False





11. A neural network is an artificial intelligence system that is capable of

finding and differentiating patterns.



a) True b) False





12. A genetic algorithm is a neural network that mimics the evolutionary,

survival-of-the-fittest process to generate increasingly better solutions

to a problem.



a) True b) False





13. A buyer agent is an intelligent agent on a Web site that helps the customer

find products and services.



a) True b) False





14. Data-mining agents observe and report on equipment.



a) True b) False





15. An expert system can be used for medical diagnosis by giving symptoms and

trying to determine what is wrong.



a) True b) False





16. A genetic algorithm follows a trial and error approach.



a) True b) False





17. Selection as it refers to evolution means giving preference to better

outcomes.



a) True b) False





18. Mutation refers to giving preference to newer outcomes.



a) True b) False





19. Agent-based modeling involves multiple intelligent agents that can adapt to

changing conditions.



a) True b) False







20. Amazon uses information agents to show products to customers hoping to

generate new purchases.



a) True b) False





Part II

Multiple Choice





21. In what decision making phase do you recognize a problem, need, or

opportunity?



a) Predication and decision

b) Choice

c) Preliminary or investigative

d) Intelligence





22. In what decision making phase do you consider possible ways of solving

problems, filling needs, or capitalizing on opportunities?



a) Design

b) Intelligence

c) Choice

d) Prediction and decision





23. In what decision making phase do you examine and weigh the merits of

solutions, estimate the consequence of each, and choose the best solution?



a) Design

b) Choice

c) Intelligence

d) Preliminary or investigative





24. There are four main types of decisions. Which one represents decisions that

always have a right answer?



a) Recurring

b) Ad hoc

c) Defined

d) Structured





25. Which of the four types of decisions occur sporadically, perhaps only once?



a) Structured

b) Nonrecurring or ad hoc

c) Nonstructured

d) Impromptu





26. Which DSS component stores and maintains the information you want your DSS

to use?



a) Query management

b) Data administration

c) Model management

d) Data management





27. If you needed to analyze the bear population in New Jersey and their

interactions with humans located in towns and cities, what type of computer

application should you use?



a) Model management

b) Expert system

c) Geographic information system

d) Multidimensional information system





28. Law enforcement agencies that use computer applications to plan and deploy

its police force probably use _____________ systems.



a) Geographic information

b) Database management systems

c) Crossover intelligent

d) Biomimicry





29. Which of the following is the science of making machines imitate human

thinking and behavior?



a) Artificial intelligence

b) Database management

c) Machine intelligence

d) Swarm management





30. Which of the following is not considered a type of artificial intelligence?



a) Expert systems

b) Neural networks

c) Geographic information systems

d) Genetic algorithms





31. What must you have before you can effectively use a DSS?



a) Fast and ample bandwidth

b) Considerable knowledge or expertise

c) Powerful systems capable of manipulating large amounts of information

d) Programming knowledge





32. What is the difference between a decision support system (DSS) and an expert

system (ES)?



a) A DSS supports the novice users; an ES supports the analyst or expert

b) The DSS requires considerable knowledge from the user; the ES provides

considerable knowledge to the user

c) The ES requires considerable storage space for the needed information;

the DSS does not

d) The DSS requires rules or domain knowledge; the ESS requires business

models





33. An expert system is capable of all but which of the following?



a) Handling massive amounts of information

b) Providing conclusive answers

c) Summarizing information from various sources

d) Working with rules





34. What can't an expert system do?



a) Learn from previous experiences the way humans can

b) Provide new information

c) Provide consistency in decision making

d) Reduce errors





35. What type of system is known for finding and differentiating patterns?



a) Neural networks

b) Expert systems

c) Geographic information systems

d) Decision support systems





36. Which type of artificial intelligent system mimics the evolutionary,

survival-of-the-fittest process to generate increasingly better solutions

to a problem?



a) Fuzzy logic

b) Genetic algorithm

c) Intelligent database management systems (I-DBMS)

d) Expert system





37. What is the difference between an expert system and a genetic algorithm?



a) An expert system uses a genetic algorithm to assist in understanding the

problem

b) An expert system provides more accurate solutions that a genetic

algorithm

c) A genetic algorithm provides you with the best solution; an expert system

provides you with many solutions along with the confidence level for each

possible solution

d) Expert systems belong in the category of artificial intelligence; genetic

algorithms work with large database and warehouse systems that are not

considered artificially intelligent





38. There are four types of intelligent agents. Which of the following is not

considered one of these types?



a) Reporting agent

b) Information agent

c) Monitoring-and-surveillance agent

d) User or personal agent







39. When NASA uses intelligent agents to observe inventory levels and help

identify and solve potential problems, NASA is using a(n) _________ agent.



a) User

b) Data-mining

c) Monitoring-and-surveillance

d) Reporting





40. What type of intelligence is based on the collective behavior of groups

of simple agents and how these groups work to solve complex and mutual

problems?



a) Group intelligence

b) Social intelligence

c) Swarm intelligence

d) Crowd behavior

Expert Systems

are computer programs that are derived from a branch of computer science research called Artificial Intelligence (AI). AI's scientific goal is to understand intelligence by building computer programs that exhibit intelligent behavior. It is concerned with the concepts and methods of symbolic inference, or reasoning, by a computer, and how the knowledge used to make those inferences will be represented inside the machine.

Expert systems

The expert system is a major application of AI today. Also known as knowledge-based systems, expert systems act as intelligent assistants to human experts or serve as a resource to people who may not have access to an expert. The major difference between an expert system and a simple database containing information on a particular subject is that the database can only give the user discrete facts about the subject, whereas an expert system uses reasoning to draw conclusions from stored information. The purpose of this AI application is not to replace our human experts, but to make their knowledge and experience more widely available.



An expert system has three parts: knowledge base, inference engine, and user interface. The knowledge base contains both declarative (factual) and procedural (rules-of-usage) knowledge in a very narrow field. The inference engine runs the system by determining which procedural knowledge to access in order to obtain the appropriate declarative knowledge, then draws conclusions and decides when an applicable solution is found.



An interface is usually defined as the point where the machine and the human "touch." An interface is usually a keyboard, mouse, or similar devices. In an expert system, there are actually two different user interfaces: One is for the designer of the system (who is generally experienced with computers) the other is for the user (generally a computer novice). Because most users of an expert system will not be computer experts, it is important that system be easy for them to use. All user interfaces are bi-directional; that is, are able to receive information from the user and respond to the user with its recommendations. The designer's user interface must also be capable of adding new information to the knowledge base.