Abduction as reasoning paradigm has been much explored in Artificial Intelligence, but not yet taken up by decision making as much as its potential warrants. Indeed, abduction permits the generation of hypothetical knowledge based scenarios, about which one can then equate decisions. One reason for this state of affairs is that abduction is difficult to implement efficaciously, even by experts, which entails that abductive systems are not readily available for decision making. Our concept of tabled abduction mitigates this, in the abductive logic programming system TABDUAL.

The contribution of this paper is three-fold: (1) We discuss some TABDUAL improvements towards its more practical use, particularly in decision making, (2) We show that declarative debugging can be viewed as abduction in logic programming, thus showing another potential of abduction for decision making, and (3) We describe how TABDUAL can be applied in decision making and examine its benefit.