
TL;DR
Fast Downward is a heuristic search-based planning system that uses multi-valued representations and hierarchical decompositions to efficiently solve complex deterministic planning problems encoded in PDDL2.2.
Contribution
It introduces a novel multi-valued planning task representation and advanced heuristic techniques, including the causal graph heuristic and multi-heuristic search, for improved planning performance.
Findings
Effective handling of PDDL2.2 features like axioms and conditional effects
Introduction of multi-heuristic best-first search for better search guidance
Development of efficient data structures for fast state expansion
Abstract
Fast Downward is a classical planning system based on heuristic search. It can deal with general deterministic planning problems encoded in the propositional fragment of PDDL2.2, including advanced features like ADL conditions and effects and derived predicates (axioms). Like other well-known planners such as HSP and FF, Fast Downward is a progression planner, searching the space of world states of a planning task in the forward direction. However, unlike other PDDL planning systems, Fast Downward does not use the propositional PDDL representation of a planning task directly. Instead, the input is first translated into an alternative representation called multi-valued planning tasks, which makes many of the implicit constraints of a propositional planning task explicit. Exploiting this alternative representation, Fast Downward uses hierarchical decompositions of planning tasks for…
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