State-variable planning under structural restrictions: algorithms and complexity
Artificial Intelligence
Applications of modern heuristic search methods to pattern sequencing problems
Computers and Operations Research
Artificial Intelligence - Special issue on heuristic search in artificial intelligence
Speeding up the calculation of heuristics for heuristic search-based planning
Eighteenth national conference on Artificial intelligence
Anytime Heuristic Searc: First Results TITLE2:
Anytime Heuristic Searc: First Results TITLE2:
Decomposition of planning problems
AI Communications
Anytime search in dynamic graphs
Artificial Intelligence
Concise finite-domain representations for PDDL planning tasks
Artificial Intelligence
Heuristics for Planning with Action Costs Revisited
Proceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 2
On-line planning and scheduling: an application to controlling modular printers
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 3
On reasonable and forced goal orderings and their use in an agenda-driven planning algorithm
Journal of Artificial Intelligence Research
The FF planning system: fast plan generation through heuristic search
Journal of Artificial Intelligence Research
PDDL2.1: an extension to PDDL for expressing temporal planning domains
Journal of Artificial Intelligence Research
Sapa: a multi-objective metric temporal planner
Journal of Artificial Intelligence Research
Journal of Artificial Intelligence Research
The fast downward planning system
Journal of Artificial Intelligence Research
Temporal planning using subgoal partitioning and resolution in SGPlan
Journal of Artificial Intelligence Research
Journal of Artificial Intelligence Research
IJCAI'89 Proceedings of the 11th international joint conference on Artificial intelligence - Volume 2
AWA*-a window constrained anytime heuristic search algorithm
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Best-first utility-guided search
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Subgoal ordering and goal augmentation for heuristic problem solving
IJCAI'87 Proceedings of the 10th international joint conference on Artificial intelligence - Volume 2
Cost-optimal planning with landmarks
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Trees of shortest paths vs. Steiner trees: understanding and improving delete relaxation heuristics
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Sound and Complete Landmarks for And/Or Graphs
Proceedings of the 2010 conference on ECAI 2010: 19th European Conference on Artificial Intelligence
Strengthening Landmark Heuristics via Hitting Sets
Proceedings of the 2010 conference on ECAI 2010: 19th European Conference on Artificial Intelligence
Sound and Complete Landmarks for And/Or Graphs
Proceedings of the 2010 conference on ECAI 2010: 19th European Conference on Artificial Intelligence
Best-first heuristic search for multicore machines
Journal of Artificial Intelligence Research
Parallel divide-and-evolve: experiments with OpenMP on a multicore machine
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Scaling up heuristic planning with relational decision trees
Journal of Artificial Intelligence Research
Exploiting macro-actions and predicting plan length in planning as satisfiability
AI*IA'11 Proceedings of the 12th international conference on Artificial intelligence around man and beyond
Full extraction of landmarks in propositional planning tasks
AI*IA'11 Proceedings of the 12th international conference on Artificial intelligence around man and beyond
Everything you always wanted to know about planning (but were afraid to ask)
KI'11 Proceedings of the 34th Annual German conference on Advances in artificial intelligence
Analyzing search topology without running any search: on the connection between causal graphs and h+
Journal of Artificial Intelligence Research
Using the relaxed plan heuristic to select goals in oversubscription planning problems
CAEPIA'11 Proceedings of the 14th international conference on Advances in artificial intelligence: spanish association for artificial intelligence
Tell me when and why to do it!: run-time planner model updates via natural language instruction
HRI '12 Proceedings of the seventh annual ACM/IEEE international conference on Human-Robot Interaction
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Three
COLIN: planning with continuous linear numeric change
Journal of Artificial Intelligence Research
Planning as satisfiability: Heuristics
Artificial Intelligence
Concise representations for state spaces in conformant planning tasks
ICICA'12 Proceedings of the Third international conference on Information Computing and Applications
Coordinating the web of services for a smart home
ACM Transactions on the Web (TWEB)
Qualitative constraint satisfaction problems: An extended framework with landmarks
Artificial Intelligence
A case-based approach to heuristic planning
Applied Intelligence
A hybrid LP-RPG heuristic for modelling numeric resource flows in planning
Journal of Artificial Intelligence Research
Revisiting regression in planning
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
An admissible heuristic for SAS+ planning obtained from the state equation
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
Fair LTL synthesis for non-deterministic systems using strong cyclic planners
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
The GoDeL planning system: a more perfect union of domain-independent and hierarchical planning
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
Plan quality optimisation via block decomposition
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
Landmark-based heuristics and search control for automated planning (extended abstract)
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
A SAT-based approach to cost-sensitive temporally expressive planning
ACM Transactions on Intelligent Systems and Technology (TIST) - Special Section on Intelligent Mobile Knowledge Discovery and Management Systems and Special Issue on Social Web Mining
Automated runtime repair of business processes
Information Systems
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LAMA is a classical planning system based on heuristic forward search. Its core feature is the use of a pseudo-heuristic derived from landmarks, propositional formulas that must be true in every solution of a planning task. LAMA builds on the Fast Downward planning system, using finite-domain rather than binary state variables and multi-heuristic search. The latter is employed to combine the landmark heuristic with a variant of the well-known FF heuristic. Both heuristics are cost-sensitive, focusing on high-quality solutions in the case where actions have non-uniform cost. A weighted A* search is used with iteratively decreasing weights, so that the planner continues to search for plans of better quality until the search is terminated. LAMA showed best performance among all planners in the sequential satisficing track of the International Planning Competition 2008. In this paper we present the system in detail and investigate which features of LAMA are crucial for its performance. We present individual results for some of the domains used at the competition, demonstrating good and bad cases for the techniques implemented in LAMA. Overall, we find that using landmarks improves performance, whereas the incorporation of action costs into the heuristic estimators proves not to be beneficial. We show that 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. The iterated weighted A* search greatly improves results, and shows synergy effects with the use of landmarks.