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Explanation Based Learning (EBL)

Humans appear to learn quite a lot from one example.

Basic idea: Use results from one examples problem solving effort next time around.

An EBL accepts 4 kinds of input:

A training example
-- what the learning sees in the world.
A goal concept
-- a high level description of what the program is supposed to learn.
A operational criterion
-- a description of which concepts are usable.
A domain theory
-- a set of rules that describe relationships between objects and actions in a domain.

From this EBL computes a generalisation of the training example that is sufficient not only to describe the goal concept but also satisfies the operational criterion.

This has two steps:

-- the domain theory is used to prune away all unimportant aspects of the training example with respect to the goal concept.
-- the explanation is generalised as far possible while still describing the goal concept.