Within a framework of a world consisting of an environment and some learning systems we need at least one task which has to be solved.

Intuitively a task is a collection of different 'states' which can be classified as 'start states' , as 'goal states' or as 'intermediate states' with

(10.1) |

A 'complete task' has at least one start state with a corresponding goal state and at least one connecting 'path' between the start and the goal state. Generally we are looking for minimally necessary states.

A state is a finite set of 'properties', each a category-value pair. Two states are different, if there exists at least one property with regard to which the two states are different.

(10.2) |

Every property of a state must be measurable, otherwise it's not existing for the theory.

States belong to an environment.

Gerd Doeben-Henisch 2013-01-14