Chapter 6 Automated And Emerging Technologies: Unit 6.3: Artificial Intelligence (AI) Flashcards
Define AI
The simulation of intelligent human behaviour by a computer.
Define narrow AI
This occurs when a machine has superior performance to a human when doing one specific task
Define general AI
This occurs when a machine is similar (not superior) in its performance to a human doing a specific task
Define strong AI
This occurs when a machine has superior performance to a human in many tasks
Define expert system
A computer system that mimics the decision-making ability of a human; expert systems use AI to simulate the judgement and behaviour of a human or organisation that has expert knowledge and experience
Name 7 applications of expert systems.
Oil and mineral prospecting
Diagnosis of a patient’s illness
Fault diagnostics in mechanical and electronic equipment
Tax and financial calculations
Strategy games (eg. Chess)
Logistics (efficient routing of parcel delivery)
Identification of plants, animals and chemical/biological compounds
What are the 9 advantages of expert systems?
High level of expertise
High accuracy
Results are consistent
Have the ability to store vast amounts of ideas and facts
Can make traceable logical solutions and diagnostics
Is possible for an expert system to have multiple expertise
Very fast response times
Provide unbiased reporting and analysis of the facts
Indicate the probability of any suggested solution being correct
What are the 5 disadvantages of expert systems?
Users of the expert system need considerable training in its use to ensure the system is being used correctly
The set up and maintenance costs are very high
Tend to give very ‘cold’ responses that may not be very appropriate in certain medical situations
They are only as good as the information/facts entered into the system
Users sometimes make the very dangerous assumption that they are infallible
What are the 5 parts that make up an expert system?
User interface
Explanation system
Inference engine
Rules base
Knowledge base
Describe the user interface
Method by which the expert system interacts with a user
Interaction can be through dialogue boxes, command prompts or other input methods
The questions being asked usually only have Yes/No answers and are based on the responses to previous questions
Describe the inference engine.
Main processing element of the expert system
Acts like a search engine examining the knowledge base for information/data that matches the queries
Responsible for gathering information from the user by asking a series of questions and applying responses where necessary; each question being asked is based on the previous responses
Is the problem-solving part of the expert system that makes use of the inference rules in the rules base
Since the knowledge base is a collection of objects and attributes, the inference engine attempts to use information gathered from the user to find an object that matches (making use of the rules base to find a match)
Describe the knowledge base.
Repository of facts
Stores all the knowledge about an area of expertise obtained from a number of expert resources
Essentially a collection of objects and their attributes
Describe the rules base.
Set of inference rules
Inference rules are used by the inference engine to draw conclusions (the methods used closely follow human reasoning)
They follow logical thinking; usually involving a series of IF statements
How is an expert system set up?
Information needs to be gathered from human experts or from written sources
Information gathered is used to populate the knowledge base that needs to be first created
A rules base needs to be created
Then the inference engine needs to be set up
The user interface needs to be developed to allow the user and expert system to communicate
Once the system is set up, it needs to be fully tested: this is done by running the system with known outcomes so that the results can be compared and any changes to the expert system made
Describe machine learning.
Sub-set of AI, in which algorithms are ‘trained’ and learn from their past experiences and examples. It is possible for the system to make predictions or even take decisions based on previous scenarios.
