www.plg.inf.uc3m.es Abstract. Oversubscription planning (OSP) appears in many real problems where finding a plan achieving all goals is infeasi-ble. The objective is to find a feasible plan reaching a goal sub-set while maximizing some measure of utility. In this paper, we present a new technique to select goals “a priori ” for problems in which a cost bound prevents all the goals from being achieved. It uses estimations of distances between goals, which are com-puted using relaxed plans. Using these distances, a search in the space of subsets of goals is performed, yielding a new set of goals to plan for. A revised planning problem can be created and solved, taking into account only the selected goals. We present experiments in six differe...
Most modern heuristics for classical planning are specified in terms of minimizing the summed operat...
AbstractWe present a heuristic search approach to solve partial satisfaction planning (PSP) problems...
In many real world planning scenarios, agents often do not have enough resources to achieve all of t...
Oversubscription planning (OSP) appears in many real problems where nding a plan achieving all goa...
Planning deals with the task of finding an ordered set of actions that achieves some goals from an i...
Oversubscription planning (OSP) is the problem of finding plans that maximize the utility value of t...
Abstract. In the basic setup of oversubscription planning (OSP), the objective is to achieve an as v...
The aim of classical planning is to minimize the summed cost of operators among those plans that ach...
While in classical planning the objective is to achieve one of the equally attractive goal states at...
A* search-based planner for Oversubscription Planning, as described in the paper A∗ Search and Boun...
The objective of optimal oversubscription planning is to find a plan that yields an end state with a...
Solving relaxed problems is a commonly used technique in heuristic search to derive heuristic estima...
Past Planning systems have generally focused on structures capable of working in all domains (domain...
The problem of searching for a plan with cost at most equal to a given absolute bound has attracted ...
When given a plan by a satisficing planner, it is usually not intuitive as to how close it is to the...
Most modern heuristics for classical planning are specified in terms of minimizing the summed operat...
AbstractWe present a heuristic search approach to solve partial satisfaction planning (PSP) problems...
In many real world planning scenarios, agents often do not have enough resources to achieve all of t...
Oversubscription planning (OSP) appears in many real problems where nding a plan achieving all goa...
Planning deals with the task of finding an ordered set of actions that achieves some goals from an i...
Oversubscription planning (OSP) is the problem of finding plans that maximize the utility value of t...
Abstract. In the basic setup of oversubscription planning (OSP), the objective is to achieve an as v...
The aim of classical planning is to minimize the summed cost of operators among those plans that ach...
While in classical planning the objective is to achieve one of the equally attractive goal states at...
A* search-based planner for Oversubscription Planning, as described in the paper A∗ Search and Boun...
The objective of optimal oversubscription planning is to find a plan that yields an end state with a...
Solving relaxed problems is a commonly used technique in heuristic search to derive heuristic estima...
Past Planning systems have generally focused on structures capable of working in all domains (domain...
The problem of searching for a plan with cost at most equal to a given absolute bound has attracted ...
When given a plan by a satisficing planner, it is usually not intuitive as to how close it is to the...
Most modern heuristics for classical planning are specified in terms of minimizing the summed operat...
AbstractWe present a heuristic search approach to solve partial satisfaction planning (PSP) problems...
In many real world planning scenarios, agents often do not have enough resources to achieve all of t...