A general formulation of abduction algorithms

The paper offers a general formulation of abduction algorithms, referred to as minimum length solution algorithms, which are based on all observable states. The algorithms compute the necessary evidence to derive the correct hypothesis in minimum steps. A first version of algorithms is proposed such that to deal with situations when not all states are observable. The development of fuzzy inference systems is presented in order to apply the minimum length solution algorithms to sets of imprecise observations.