Recently, planning based on answer set programming has been proposed as an approach towards realizing declarative planning systems. In this paper, we present the language K extends the declarative planning language K by action costs. K provides the notion of admissible and optimal plans, which are plans whose overall action costs are within a given limit resp.

I introduce a new search heuristic for propositional STRIPS planning that is based on transforming planning instances to linear programming instances. The linear programming heuristic is admissible for finding minimum length plans and can be used by partial-order planning algorithms. This heuristic appears to be the first non-trivial admissible heuristic for partial-order planning. An empirical study compares Lplan, a partial-order planner incorporating the heuristic, to Graphplan, Satplan, and UCPOP on the tower of Hanoi domain, random blocks-world instances, and random planning instances. Graphplan is far faster in the study than the other algorithms. Lplan is often slower because the heuristic is time-consuming, but Lplan shows promise because it often performs a small search. Introduction Planning is the problem of finding a combination of actions that achieves a goal (Allen, Hendler, & Tate 1990; Hendler, Tate, & Drummond 1990). So far, there is limited success in general-purpose...

Resources such as food, hit points or magical power are standard features of today's computer games. Computer-guided characters often have goals that are related to these resources and must take this into account in planning their behavior. In the field of artificial intelligence, resource-based action planning systems have recently begun to mushroom. However, these systems still tend to neglect resources. Conventional plan length is the primary optimization goal, resources being of only secondary importance. This paper illustrates the problem and gives an overview of the Excalibur agent's planning system, which overcomes these deficiencies by applying an extended constraint programming framework to planning. It allows the search space to be explored without the need to focus on plan length, makes it possible to optimize other criteria like resource-related properties and promotes the inclusion of domain-dependent knowledge to guide and accelerate the search for a plan.

... This paper presents the key ideas underlying this approach.