Inductive learning of answer set programs for autonomous surgical task planning

Inductive Learning of Answer Set Programs

Adding Domain Dependent Knowledge into Answer Set Programs for Planning

We investigate the methodology of utilizing domain dependent knowledge in solving the planning problem in answer set programming. We provide a classification of domain dependent knowledge, and for each class, a coding scheme. In this way, domain dependent knowledge can be encoded into an existing program. Experiments are conducted to illustrate the effect of adding domain dependent knowledge fo...

Communicating Answer Set Programs

Answer set programming is a form of declarative programming that has proven very successful in succinctly formulating and solving complex problems. Although mechanisms for representing and reasoning with the combined answer set programs of multiple agents have already been proposed, the actual gain in expressivity when adding communication has not been thoroughly studied. We show that allowing ...

Planning in Answer Set Programming Using Ordered Task Decomposition

In this paper we investigate a formalism for solving planning problems based on ordered task decomposition using Answer Set Programming (ASP). Our planning methodology is an adaptation of Hierarchical Task Network (HTN) planning, an approach that has led to some very efficient planners. The ASP paradigm evolved out of the stable semantics for logic programs in recent years and is strongly relat...

Answer Set Planning

In \answer set programming," solutions to a problem are represented by answer sets, and not by answer substitutions produced in response to a query, as in conventional logic programming. Instead of Prolog, answer set programming uses software systems capable of computing answer sets. This paper is about applications of this idea to planning.