To enable efficient abduction even for observations that are faulty or inadequately modeled, a relaxed abduction problem is proposed in order to explain the largest possible part of the observations with as few assumptions as possible. On the basis of two preference orders over a subset of observations and a subset of assumptions, tuples can therefore be determined such that the theory, together with the subset of assumptions, explains the subset of observations. The formulation as a multi-criteria optimization problem eliminates the need to offset assumptions made and explained observations against one another. Due to the technical soundness of the approach, specific properties of the set of results (such as correctness, completeness etc.), can be checked, which is particularly advantageous in safety-critical applications. The complexity of the problem-solving process can be influenced and therefore flexibly adapted in terms of domain requirements through the selection of the underlying representation language and preference relations. The invention can be applied to any technical system, e.g. plants or power stations.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A method of actuating a technical system, the method comprising: determining, by a data processor, a relaxed abduction problem; solving, by the data processor, the relaxed abduction problem; and actuating the technical system according to the solution of the relaxed abduction problem. 2. The method as claimed in claim 1, further comprising determining, by the data processor, tuples by taking as a basis two orders of preference over a subset of observations and a subset of assumptions, so that a theory together with the subset of the assumptions explains the subset of the observations. 3. The method as claimed in claim 2, in which the relaxed abduction problem is determined to be RAP=(T, A, O, <A, <O), wherein the theory is T, a set of abducible axioms is A, a set of observations is O with TO , and further comprising taking orders of preference <A⊂P(A)×P(A) and <O⊂P(O)×P(O) as a basis for determining <-minimal tuples (A, O)∈P(A)×P(O), so that T∪A is consistent and t∪A|=O holds. 4. The method as claimed in claim 2, in which the relaxed abduction problem is solved by transforming the relaxed abduction problem into a hypergraph, so that the tuples (A, O) are encoded by pareto-optimal paths in the hypergraph. 5. The method as claimed in claim 4, wherein the pareto-optimal paths are determined via a label approach. 6. The method as claimed in claim 4, further comprising inducing hyperedges of the hypergraph by transcriptions of prescribed rules. 7. The method as claimed in claim 6, wherein the prescribed rules are determined as follows: A ⊑ A 1 A ⊑ B  [ A 1 ⊑ B ∈  ] ( CR1 ) A ⊑ A 1  A ⊑ A 2 A ⊑ B  [ A 1 ⊓ A 2 ⊑ B ∈  ] ( CR2 ) A ⊑ A 1 A ⊑ ∃ r . B  [ A 1 ⊑ ∃ r · B ∈  ] ( CR3 ) A ⊑ ∃ · A 1  A 1 ⊑ A 2 A ⊑ B  [ ∃ r · A 2 ⊑ B ∈  ] ( CR4 ) A ⊑ ∃ r 1 · B A ⊑ ∃ s · B  [ r 1 ⊑ s ∈  ] ( CR5 ) A ⊑ ∃ r 1 · A 1  A 1 ⊑ ∃ r 2 · B A ⊑ ∃ s · B  [ r 1 ∘ r 2 ⊑ s ∈  ] ( CR6 ) 8. The method as claimed in claim 4, wherein a weighted hypergraph HRAP=(V, E), which is induced by the relaxed abduction problem, is determined by V={(AB),(A∃r.B) |A, B ∈NCT, r ∈NR}, wherein VT={(AA),(AT)|A∈NCT}⊂V denotes a set of final states and E denotes a set of the hyperedges e=(T(e), h(e), w(e)), so that the following holds: an axiom a∈T∪A exists that justifies derivation h(e)∈V from T(e)⊂V based on one of the prescribed rules, wherein the edge weight w(e) is determined according to A = { { a } if   a ∈ A , ∅ otherwise   O = { { h  ( e ) } if   h  ( e ) ∈ O , ∅ otherwise 9. The method as claimed in claim 8, wherein pX,t=(VX,t,EX,t) is determined as a hyperpath in H=(V, E) from X to t if (1) t∈X and pX,t=({t}, ) or (2) there is an edge e∈E, so that h(e)=t, T(e)={y1, . . . , yk} holds. 10. The method as claimed in claim 9, wherein shortest hyperpaths are determined by taking account of two preferences. 11. The method as claimed in claim 10, wherein the shortest hyperpaths are determined by taking account of two preferences via a label correction algorithm. 12. The method as claimed in claim 11, wherein the labels encode pareto-optimal paths to the hitherto found nodes of the hypergraph. 13. The method as claimed in claim 12, wherein alterations along the hyperedges are propagated by a meet operator and/or by a join operator. 14. The method as claimed in claim 1, wherein the relaxed abduction problem is determined via a piece of description logic. 15. An apparatus for actuating a technical system by the data processor performing the method as claimed in claim 1.