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Up: What is Learning?
Previous: What is Learning?
Many approaches have been taken to attempt to provide a machine with learning
capabilities. This is because learning tasks cover a wide range of phenomena.
Listed below are a few examples of how one may learn. We will look at these in
- Skill refinement
- -- one can learn by practicing, e.g playing the
- Knowledge acquisition
- -- one can learn by experience and by storing the
experience in a knowledge base. One basic example of this type is rote
- Taking advice
- -- Similar to rote learning although the knowledge that
is input may need to be transformed (or operationalised) in order to be
- Problem Solving
- -- if we solve a problem one may learn from this
experience. The next time we see a similar problem we can solve it more
efficiently. This does not usually involve gathering new knowledge but may
involve reorganisation of data or remembering how to achieve to solution.
- -- One can learn from examples. Humans often classify
things in the world without knowing explicit rules. Usually involves a teacher
or trainer to aid the classification.
- -- Here one learns knowledge without the aid of a teacher.
- -- If a system can recognise similarities in information
already stored then it may be able to transfer some knowledge to improve to
solution of the task in hand.