Question 1

A fundamental difference between a data mining approach to problem solving and an expert systems approach is&#10;A) the output of an expert system is a set of rules and the output of a data mining technique is a decision tree.&#10;B) a data mining technique builds a model without the aid of a human expert.&#10;C) a model built using a data mining technique can explain how decisions are made but an expert system cannot.&#10;D) an expert system is built using inductive learning whereas a data mining model is built using one or several deductive techniques

Accepted Answer

A data mining approach to problem solving involves building a model or discovering patterns in data without the aid of a human expert, while an expert systems approach relies on the knowledge and expertise of a human expert to create a set of rules for decision making. Therefore, option B correctly distinguishes between the two approaches. Option A is incorrect because both techniques can generate a decision tree as output. Option C is incorrect because both techniques can provide explanations for their output. Option D is incorrect because while deductive techniques can be used in data mining, not all data mining models are developed deductively and expert systems are not necessarily developed through inductive learning.

Question 2

Autonomy is an agent's ability to&#10;A) react to a changing environment.&#10;B) act without direct intervention from others.&#10;C) confer with other agents.&#10;D) react to sensory information received from the environment.

Accepted Answer

Autonomy refers to the ability to act without direct intervention from others.

Other options (A, C, D) describe aspects of an agent's behavior, but do not specifically address the concept of autonomy.

Question 3

Data mining techniques and intelligent agents are similar in that they&#10;A) are both used for hypotheses testing.&#10;B) both have the ability to learn.&#10;C) are goal directed.&#10;D) both build models from data.

Accepted Answer

Both data mining techniques and intelligent agents have the ability to learn from data or their environment, adapting their actions or predictions over time based on the information they process.

Question 4

An agent's ability to choose its actions in the context of other agents.&#10;A) autonomy&#10;B) cooperation&#10;C) adaptivity&#10;D) coordination

Accepted Answer

Coordination refers to the agent's ability to choose its actions in the context of other agents, by taking into account their actions, goals, and beliefs. It is important for the agents to coordinate their actions towards a common goal in order to achieve better results. Autonomy refers to the agent's ability to act independently, without the need for external control or intervention. Cooperation refers to the agent's ability to work together towards a common goal, without necessarily considering the actions of other agents. Adaptivity refers to the agent's ability to adjust its behavior to changing environments or situations.

Question 5

This type of agent resides inside a data warehouse in an attempt to discover changes in business trends.&#10;A) semiautonomous agent&#10;B) cooperative agent&#10;C) data mining agent&#10;D) filtering agent

Accepted Answer

A data mining agent is specifically designed to discover underlying patterns and trends within a large dataset. They are often used within data warehouses to identify changes in business trends and provide insights for decision-making. Semiautonomous agents are capable of making decisions on their own, while cooperative agents work with other agents to achieve a common goal. Filtering agents are used to sift through information and prioritize it based on certain criteria.

Question 6

An expert system contains _________ knowledge whereas the knowledge processed by an intelligent agent is _____________&#10;A) personal, general&#10;B) general, personal&#10;C) direct, indirect&#10;D) indirect, direct

Accepted Answer

An expert system contains general knowledge, which is often domain-specific and is programmed by human experts in a particular field of study. On the other hand, the knowledge processed by an intelligent agent is personal, as it is acquired through interactions with its environment and tailored to the specific needs of the agent. Therefore, option B is the best choice as it correctly identifies the type of knowledge used in each system.

Deck 14: Intelligent Agents