Open AccessProceedings Article
Abstracting abstraction in search with applications to planning
Christer Bäckström,Peter Jonsson +1 more
- pp 446-456
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A coherent and flexible framework for modelling abstraction (and abstraction-like) methods based on transformations on labelled graphs that can capture many search abstraction concepts and that can put them into a broader context.Abstract:
ion has been used in search and planning from the very beginning of AI. Many different methods and formalisms for abstraction have been proposed in the literature but they have been designed from various points of view and with varying purposes. Hence, these methods have been notoriously difficult to analyse and compare in a structured way. In order to improve upon this situation, we present a coherent and flexible framework for modelling abstraction (and abstraction-like) methods based on transformations on labelled graphs. Transformations can have certain method properties that are inherent in the abstraction methods and describe their fundamental modelling characteristics, and they can have certain instance properties that describe algorithmic and computational characteristics of problem instances. The usefulness of the framework is demonstrated by applying it to problems in both search and planning. First, we show that we can capture many search abstraction concepts (such as avoidance of backtracking between levels) and that we can put them into a broader context. We further model five different abstraction concepts from the planning literature. Analysing what method properties they have highlights their fundamental differences and similarities. Finally, we prove that method properties sometimes imply instance properties. Taking also those instance properties into account reveals important information about computational aspects of the five methods.read more
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References
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Journal ArticleDOI
Planning in a hierarchy of abstraction spaces
TL;DR: Examples of the ABSTRIPS system's performance are presented that demonstrate the significant increases in problem-solving power that this approach provides, and some further implications of the hierarchical planning approach are explored.
Journal ArticleDOI
Planning as search: a quantitative approach
TL;DR: It is presented that planning can be viewed as problem-solving search using subgoals, macro-operators, and abstraction as knowledge sources and an analysis of abstraction concludes that abstraction hierarchies can reduce exponential problems to linear complexity.
Journal ArticleDOI
Automatically generating abstractions for planning
TL;DR: A completely automated approach to generating abstractions for planning using a tractable, domain-independent algorithm whose only input is the definition of a problem to be solved and whose output is an abstraction hierarchy that is tailored to the particular problem.
Journal ArticleDOI
Ordered landmarks in planning
TL;DR: 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.