6.3 Artificial intelligence

What is AI:

The development of programs to simulate human behaviour. Including:

  • Image recognition: identifies objects or people in an image
  • Speech recognition: identifies words spoken and stores them
  • Natural language: receives commands or instructions that are not in a set format and perform the required response
  • Computer games: move elements or characters independently based on the environment
  • Diagnosis systems: used to diagnose certain conditions, eg. Using a patients symptoms to detect the illness and suggest actions to cure

Components of AI:

  • Collection of data
  • A set of programmed rules
  • The ability to reason
  • The ability to learn and adapt

Describe the characteristics of AI

  • Collects data
    Stores rules for using the data
  • Has the ability to reason
  • Has the ability to learn by using machine learning
  • ..by adapting what it does
  • ..for example from
  • mistakes previously made, to not make them again
  • ..by changing its own rules
  • ..by changing its own data
  • ..by being trained
  • Makes one or more predictions(to make a decision)
  • Find/analyse patterns

What is machine learning

  • Is when a program has the ability to automatically adapt its own processes and/or data

Explain how a program can use AI to help a robot solve different puzzles

  • Use machine learning algorithms
  • Collects data about where it has been
  • Collects data about obstacles
  • Stores successful actions
    Stores unsuccessful actions
  • Identifies and stores patterns
  • ..make sure it does not repeat incorrect rout
  • ..so it knows how to react to obstacles next time
  • ..so it knows what is most likely to work next time

What is an expert system?

  • A special type of system that attempts to emulate the expertise of a human.
  • Achieved by asking questions to determine the solution to the answer
  • Depending on the choices the system will ask a different question

Expert system Key features/components

Knowledge base:

  • a repository of facts
  • a collection of objects and their attributes

 

Rule base:

  • a collection of inference rules used to draw conclusions
  • inference rules are used by the inference engine to draw conclusions

 

Inference engine:

  • a kind of search engine used in an expert system which examines the knowledge base for information that matches the queries
  • the inference engine is the problem-solving part of the expert system that makes use of inference rules in the rules base

 

Interface:

  • used to allow the user to interact with the expert system
    interaction can be through dialogue boxes, command prompts or other input methods

Why does an expert system need a knowledge base?

  • It needs facts..
  • ..to generate the rules
  • ..to make the decisions//The data it contains is essential to the decision making process

Advantages of Expert systems

  • they offer a high level of expertise

  • they offer high accuracy

  • the results are consistent

  • they have the ability to store vast amounts of ideas and facts

  • they can make traceable logical solutions and diagnostics
    it is possible for an expert system to have multiple expertise

  • they have very fast response times (much quicker than a human expert)

  • they provide unbiased reporting and analysis of the facts

  • they indicate the probability of any suggested solution being correct.

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
  • they tend to give very ‘cold’ responses that may not be 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.