Recent discoveries in automated planning are broadening the scope of planners, from toy
problems to real applications. However, applying automated planners to real-world …

Generalized planning is the task of generating a single solution (a generalized plan) that is
valid for multiple planning instances. In this paper we introduce a novel formalism for …

In recent years the field of Automated Planning has significantly advanced and several
powerful domain-independent planners have been developed. However, none of these …

Current evaluation functions for heuristic planning are expensive to compute. In numerous
planning problems these functions provide good guidance to the solution, so they are worth …

We present a novel approach for decreasing state uncertainty in planning prior to solving the
planning problem. This is done by making predictions about the state based on currently …

Planning and Learning under Uncertainty Page 1 Universidad Carlos III de Madrid TESIS
DOCTORAL Planning and Learning under Uncertainty Autor Sergio Jiménez Celorrio Directores …

In Automated planning, learning and exploiting additional knowledge within a domain
model, in order to improve the performance of domain-independent planners, has attracted …

The computation of relaxed plans provides valuable information about the solution to a
planning problem in polynomial time. Moreover, in some domains relaxed plans can be …

Resumen La Planificación Generalizada es el problema de encontrar una solución en forma
de algoritmo llamada plan generalizado a múltiples instancias de planificación. Las …

This chapter reports the last machine learning techniques for the assistance of automated
planning. Recent discoveries in automated planning have opened the scope of planners …