Unavoidable dead-ends are common in many probabilistic planning problems, eg when
actions may fail or when operating under resource constraints. An important objective in …

For the past 25 years, heuristic search has been used to solve domain-independent
probabilistic planning problems, but with heuristics that determinise the problem and ignore …

We address the class of probabilistic planning problems where the objective is to maximize
the probability of reaching a prescribed goal. The complexity of probabilistic planning …

We consider the problem of generating optimal stochastic policies for Constrained
Stochastic Shortest Path problems, which are a natural model for planning under uncertainty …

Heuristic search is a powerful approach that has successfully been applied to a broad class
of planning problems, including classical planning, multi-objective planning, and …

Defining financial goals and formulating actionable plans to achieve them are essential
components for ensuring financial health. This task is computationally challenging, given the …

In CPP, we are given a set of actions (assumed deterministic in this paper), a distribution
over initial states, a goal condition, and a real value 0< θ≤ 1. We seek a plan π such that …

Stochastic shortest path problems (SSPs) capture probabilistic planning tasks with the
objective of minimizing expected cost until reaching the goal. One of the strongest methods …

Web service composition (WSC) is the task of generating new composite web services that
exhibit functionalities not supported by any single web service. In its simplest form this is …

Observation decoding aims at discovering the underlying state trajectory of an acting agent
from a sequence of observations. This task is at the core of various recognition activities that …