Answer Set Planning refers to the use of Answer Set Programming (ASP) to compute plans,
that is, solutions to planning problems, that transform a given state of the world to another …

We present a general approach to planning with incomplete information in Answer Set
Programming (ASP). More precisely, we consider the problems of conformant and …

Abstract Knowledge compilation is a valuable tool for dealing with the computational
intractability of propositional reasoning. In knowledge compilation, a representation in a …

We investigate conjunctive normal form (CNF) encodings of a function represented with a
decomposable negation normal form (DNNF). Several encodings of DNNFs and decision …

Nondeterministic planning is the process of computing plans or policies of actions achieving
given goals, when there is nondeterministic uncertainty about the initial state and/or the …

From an empirical point of view, the hardness of quantified Boolean formulas (QBFs), can be
characterized by the (in) ability of current state-of-the-art QBF solvers to decide about the …

Abstract Answer Set Planning refers to the use of Answer Set Programming (ASP) to
compute plans, that is, solutions to planning problems, that transform a given state of the …

Classical planning is the problem of finding a sequence of actions that achieves a goal,
starting from a particular initial situation. A wide range of problems can be expressed in this …

Autonomous agents that act in the real-world can often improve their success by capturing
the uncertainty that arises because of their imperfect knowledge and potentially faulty …

Conformant planning is one of the most exciting research areas of AI planning. Conformant
planning has been applied in aeronautics and space, robot control, and intelligent system …