Training Examples

The ability to learn how to solve different problems fast is understanding. The understanding cannot be programmed manually, but it can be trained.

Combinatorial AI is compatible with ELEPHANT approach to training. ELEPHANT is an open-source project on how to train machine understanding. The method features:

  • Step-by-step training from simple to complex
  • Making use of automated hypotheses generation and trial
  • Adapting to user-defined languages of subject domains
  • The continued evolution of knowledge for solving problems

The training method comprises 4 principles the development of machine understanding is based on:

  • Narrowing the search area
  • Training on examples
  • Nesting in problems and solutions
  • Reusing language structures

The principles can be used separately or in combinations.

A program example that trains AI to understand arithmetics shows the above principles at work. The supporting materials:

  • light up the role of each principle in the training process
  • explain how the principles can be realized in the training programs
  • give an operational definition to the concept of machine understanding as a characteristic of learning behavior

The training examples can serve to spread the use of machine understanding into different subject domains.