Landmarks Revisited

  title={Landmarks Revisited},
  author={Silvia Richter and M. Helmert and M. Westphal},
Landmarks for propositional planning tasks are variable assignments that must occur at some point in every solution plan. We propose a novel approach for using landmarks in planning by deriving a pseudo-heuristic and combining it with other heuristics in a search framework. The incorporation of landmark information is shown to improve success rates and solution qualities of a heuristic planner. We furthermore show how additional landmarks and orderings can be found using the information present… Expand
Admissible heuristic with multi-landmarks counting
  • L. Li, L. Weisheng
  • Computer Science
  • 2011 6th IEEE Joint International Information Technology and Artificial Intelligence Conference
  • 2011
An multi-path dependent heuristic which restricts the fact landmarks to be achieved from the current state during the search with considering the repeatedly appearance of action landmarks is proposed and proved theoretically admissible and empirically efficient. Expand
Cost-Optimal Planning with Landmarks
This work proposes a methodology for deriving admissible heuristic estimates for cost-optimal planning from a set of planning landmarks, and presents a simple best-first search procedure exploiting such heuristics. Expand
The LAMA Planner Using Landmark Counting in Heuristic Search
LAMA is a propositional planning system based on heuristic search. Its core feature is the use of a pseudo-heuristic derived from landmarks, propositions that must be true in every solution of aExpand
Viewing Landmarks as Temporally Extended Goals
Landmarks are facts that must hold true at some point in all solutions to a planning problem. The exploitation of landmarks and associated ordering constraints has been shown to be very effective inExpand
On the Inference of Intermediate Goals in Automated Planning
Using intermediate goals to guide the search or decompose a problem into smaller instances has proved to be a successful approach in Automated Planning. Goal subsets and more recently landmarks haveExpand
Exploiting Cyclic Dependencies in Landmark Heuristics
Two novel heuristics for costoptimal planning are proposed that consider cyclic dependencies between landmarks in addition to the cost for achieving all landmarks. Expand
Enhancing SAT Based Planning with Landmark Knowledge
It turns out that landmark knowledge can be beneficial, but performance highly depends on the planning domain and the planning problem itself. Expand
Exploiting Landmarks for Hybrid Planning 1
Very recently, the well-known concept of landmarks has been adapted from the classical planning setting to hierarchical planning. It was shown how a pre-processing step that extracts local landmarksExpand
The LAMA Planner: Guiding Cost-Based Anytime Planning with Landmarks
It is found that using landmarks improves performance, whereas the incorporation of action costs into the heuristic estimators proves not to be beneficial, and in some domains a search that ignores cost solves far more problems, raising the question of how to deal with action costs more effectively in the future. Expand
On the Use of Temporal Landmarks for Planning with Deadlines
The experimental results will show that this approach is helpful to quickly detect unsolvable problems and it is also very effective to solve problems with deadlines in comparison to other state-of-the-art planners. Expand


On the extraction, ordering, and usage of landmarks in planning
This work defines ordering constraints not only over the top level goals, but also over the sub-goals that will arise during planning, and demonstrates that the approach can yield significant performance improvements in both heuristic forward search and Graphplan-style planning. Expand
Ordered Landmarks in Planning
This work extends Koehler and Hoffmann's definition of reasonable orders between top level goals to the more general case of landmarks and shows how landmarks can be found, how their reasonable orders can be approximated, and how this information can be used to decompose a given planning task into several smaller sub-tasks. Expand
Extending landmarks analysis to reason about resources and repetition
Work in progress to extend some features of domain analysis using landmarks, including the extraction of resource abstracted landmarks; and the identification of landmark repetition along with a count of the minimum number of times a landmark will need to be repeated. Expand
Landmark Extraction via Planning Graph Propagation
The planner GRAPHPLAN is based on an efficient propagation of reachability information which then effectively guides a search for a valid plan. We propose a framework in which a broader class ofExpand
The FF Planning System: Fast Plan Generation Through Heuristic Search
A novel search strategy is introduced that combines hill-climbing with systematic search, and it is shown how other powerful heuristic information can be extracted and used to prune the search space. Expand
The Fast Downward Planning System
  • M. Helmert
  • Computer Science, Mathematics
  • J. Artif. Intell. Res.
  • 2006
A full account of Fast Downward's approach to solving multivalued planning tasks is given and a new non-heuristic search algorithm called focused iterative-broadening search, which utilizes the information encoded in causal graphs in a novel way is presented. Expand
State-Variable Planning Under Structural Restrictions: Algorithms and Complexity
This work identifies restrictions on the underlying state-transition graph which can tractably be tested and presents a planning algorithm which is correct and runs in polynomial time under these restrictions, and presents an exhaustive map of the complexity results for planning under all combinations of four previously studied syntactical restrictions and five new structural restrictions. Expand
A Planning Heuristic Based on Causal Graph Analysis
This paper proposes translating STRIPS problems to a planning formalism with multi-valued state variables in order to expose this underlying causal structure of the domain, and shows how this structure can be exploited by an algorithm for detecting dead ends in the search space and by a planning heuristic based on hierarchical problem decomposition. Expand
This article provides a complete map over the complexity of SAS+ planning under all combinations of the previously considered restrictions and proves that the SAS+‐PUS problem is the maximal tractable problem under the restrictions. Expand
Concise finite-domain representations for PDDL planning tasks
We introduce an efficient method for translating planning tasks specified in the standard PDDL formalism into a concise grounded representation that uses finite-domain state variables instead of theExpand