For many years, the intuitions underlying partial-order planning were largely taken for granted. Only in the past few years has there been renewed interest in the fundamental principles underlying this paradigm. In this paper, we present a rigorous comparative analysis of partial-order and total-order planning by focusing on two speci c planners that can be directly compared. We show that there are some subtle assumptions that underly the wide-spread intuitions regarding the supposed e ciency of partial-order planning. For instance, the superiority of partial-order planning can depend critically upon the search strategy and the structure of the search space. Understanding the underlying assumptions is crucial for constructing e cient planne...
We describe some simple domain-independent improvements to plan-refinement strategies for well-found...
In this document we will continue a line of research which focusses on reviving partial order planni...
Recently, several researchers have demonstrated domains where partially-ordered planners outperform ...
For many years, the intuitions underlying partial-order planning were largely taken for granted. Onl...
Although task reduction (HTN) planning historically preceded partial order (PO) planning, and is und...
AbstractDespite the long history of classical planning, there has been very little comparative analy...
For our case, we'll explore partial-order planning in a classical planning environment. Such an...
Most current partial-order planning systems are based on either the TWEAK or SNLP planning al-gorith...
When planning problems have many kinds of resources or high concurrency, each optimal state has exp...
We describe some simple domain-independent improvements to plan-refinement strategies for well-found...
The common wisdom that goal orderings can be used to improve planning performance is nearly as old a...
This paper shows an approach to profit from type information about planning objects in a partial-ord...
The common wisdom that goal orderings can be used to improve planning performance is nearly as old a...
Many known planning tasks have inherent constraints concerning the best order in which to achieve th...
Partial order reduction is a state space pruning approach that has been originally introduced in com...
We describe some simple domain-independent improvements to plan-refinement strategies for well-found...
In this document we will continue a line of research which focusses on reviving partial order planni...
Recently, several researchers have demonstrated domains where partially-ordered planners outperform ...
For many years, the intuitions underlying partial-order planning were largely taken for granted. Onl...
Although task reduction (HTN) planning historically preceded partial order (PO) planning, and is und...
AbstractDespite the long history of classical planning, there has been very little comparative analy...
For our case, we'll explore partial-order planning in a classical planning environment. Such an...
Most current partial-order planning systems are based on either the TWEAK or SNLP planning al-gorith...
When planning problems have many kinds of resources or high concurrency, each optimal state has exp...
We describe some simple domain-independent improvements to plan-refinement strategies for well-found...
The common wisdom that goal orderings can be used to improve planning performance is nearly as old a...
This paper shows an approach to profit from type information about planning objects in a partial-ord...
The common wisdom that goal orderings can be used to improve planning performance is nearly as old a...
Many known planning tasks have inherent constraints concerning the best order in which to achieve th...
Partial order reduction is a state space pruning approach that has been originally introduced in com...
We describe some simple domain-independent improvements to plan-refinement strategies for well-found...
In this document we will continue a line of research which focusses on reviving partial order planni...
Recently, several researchers have demonstrated domains where partially-ordered planners outperform ...