ITS662: INTELLIGENT SYSTEMS DEVELOPMENT
TUTORIAL: INTRODUCTION TO AI
PART A
1. Draw a mind map of an example any intelligent system development. All the element of the
Artificial Intelligent technique must be discussed together with the function, purpose and the
urgency to have the automated system. Provide the reason why the system is differ from the
conventional system.
ANSWER:
2. A café in UiTM Cawangan Melaka Kampus Jasin have a problem in managing the staff schedule
since they have morning shift and evening shift. How an Artificial Intelligence assist this café in
managing the schedule? Justify your answer and techniques suitable to reduce the problem.
Explain advantage and disadvantage of applying the technique in this problem situation.
ANSWER:
An AI-powered scheduling system based on machine learning algorithms can greatly
assist a café in managing staff schedules efficiently and effectively. By automating the
scheduling process and leveraging historical data on staff availability, preferences, and
performance, machine learning models can optimize shift allocations, adapt to changing
scheduling requirements, and reduce conflicts such as overlapping shifts or staff burnout. This
results in improved operational efficiency, better utilization of staff resources, and increased
flexibility in managing schedules to meet customer demand. However, it is important to
consider factors such as data availability, training, and maintenance requirements when
implementing such a system. Data quality and quantity, expertise in data science for model
development and training, and ongoing maintenance efforts are crucial for the success of the
AI-powered scheduling system. Despite these potential challenges, the advantages of using AI
for staff scheduling, such as automation, efficiency, flexibility, and conflict resolution,
outweigh the potential disadvantages, making it a promising solution for addressing the
scheduling problem in the café.
3. Explain how Turing Test works in determining the Artificial Intelligence System is succeed. You
may draw the situation to support your explanation in Turing Test process.
ANSWER:
Setup: The evaluator engages in conversations with both the machine and a human
through a computer interface, without knowing which is which.
Conversations: The evaluator asks a series of questions or engages in a conversation
on a specific topic with both the machine and the human. The machine responds to the
questions or engages in the conversation using its AI capabilities, while the human
responds naturally.
Responses: The machine's responses are generated by its AI algorithms and can vary
depending on the level of sophistication and capabilities of the AI system.
Evaluation: The evaluator carefully reviews the responses from both the machine and
the human and tries to determine which is which. The evaluator assesses the quality,
coherence, and naturalness of the responses to determine if they exhibit human-like
intelligence or not.
Determination: If the evaluator cannot reliably distinguish between the machine and
the human based on their responses, the machine is considered to have passed the Turing
Test and is considered to have exhibited human-like intelligence. If the evaluator can
consistently identify which is the machine, then it is considered to have not passed the
Turing Test.
4. You are a consultant in IT company who responsible to enhance the conventional becoming an
Artificial Intelligence System. How could you suggest a system which only manage recorded data
of hotel list only becoming an Artificial Intelligence system? Justify your suggestion and
expected outcome.
ANSWER:
As an IT consultant, I would suggest the following steps to transform a conventional system
managing recorded data of hotel lists into an Artificial Intelligence (AI) system:
Firstly, the recorded data of hotel lists would need to be integrated into a central repository,
such as a database or data lake, and cleaned and structured for machine learning. Next, the data
should be labeled with relevant information to create a labeled training dataset for machine
learning models. These models, such as decision trees, support vector machines, or neural
networks, can be developed using the labeled data to learn patterns and relationships in the
data. Additionally, NLP capabilities, such as text extraction, sentiment analysis, and named
entity recognition, should be integrated to enable the system to understand and process natural
language queries.
Secondly, an AI-powered recommendation engine can be developed to provide personalized
hotel recommendations based on user preferences, search queries, and historical data. This
recommendation engine can leverage machine learning models to provide personalized
suggestions, making the system more intelligent and user-friendly. The expected outcomes of
this transformation would include improved user experience, increased efficiency and accuracy,
personalization, scalability, and a competitive advantage for the IT company.
In conclusion, transforming a conventional system managing recorded data of hotel lists into an
AI system requires integrating and structuring the data, developing machine learning models,
incorporating NLP capabilities, and creating a recommendation engine. This transformation can
result in a more intelligent and user-friendly system that provides personalized hotel
recommendations, increases efficiency, and offers a competitive advantages in the market.
PART B
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a. Intelligence is an ability to LEARN and understand, to solve problem and to make decisions.
b. In Turing Test,
INTERROGATOR
c.
was a rule-based expert system for the diagnosis of infectious blood diseases.
d.
MYCIN
PROSPECTOR
was an expert system for mineral exploration developed by the Stanford
ResearchInstitute.
e. Expert systems are restricted to a very
f.
is the person who decide between machine and human.
NARROW
Expert systems have difficulty in recognising domain
domain of expertise.
BOUNDARIES
.
g. Artificial Intelligence is a science to make MACHINES do things that would require intelligence if
done by humans.
h.
SPECTROR determine the molecular structure of Martian soil, based on the mass spectral data
provided by a mass spectrometer.
i.
A computer program that can perform at a human expert level is called
j.
Among nearly 200 expert systems, most of the applications found in 1994 were in the field of
MEDICAL diagnosis.
EXPERT systems.