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Pattern Databases: Multiple Patterns For Planning And Optimization.pdf

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Preview of Pattern Databases: Multiple Patterns for Planning and Optimization
🔗 Source: ai.dmi.unibas.ch
📊 Size: 190 KB
👤 Author: Malte Helmert and Gabriele Röger
⬇️ Downloads: 65

Summary

E7. Pattern Databases: Multiple Patterns

This section explores the use of multiple pattern databases in planning and optimization, focusing on how to combine their heuristics effectively while minimizing computational overhead.

Key Concepts:

Additivity: The ability of combining heuristics from multiple patterns to produce a better estimate than any individual heuristic.
 Canonical Heuristic Function: The best possible admissible heuristic derived from a pattern collection using additivity. It's calculated by maximizing the sum of heuristics within maximal cliques of the compatibility graph formed from the patterns.
Dominated Additive Sets: A set of patterns where each pattern is a superset of at least one other. The dominant pattern's heuristic provides an upper bound for the entire set, allowing for more efficient computation.

Benefits of Using Multiple Patterns:

Improved Heuristics: Combining patterns allows for more accurate and robust heuristics than using a single pattern database.
Reduced Search Space: By leveraging additivity, planners can prune parts of the search space that are unlikely to lead to optimal solutions.

Challenges:

Computational Complexity: Evaluating multiple heuristics at each search node increases computational cost. Techniques like dominated additive sets help mitigate this.

Techniques for Efficient Implementation:

Precomputation: Store and reuse heuristic values for commonly used patterns to avoid redundant calculations.
 Dominated Sum Theorem: This theorem guarantees that the sum of heuristics from a dominated additive set is bounded by the heuristic of the dominant pattern, enabling more efficient computation.

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Description

This section of the course explores advanced heuristic techniques for planning and optimization using pattern databases, focusing on managing complexity through additivity, dominated sets, and redundant patterns to enhance efficiency in automated planning.

Technical Information

  • File Format: PDF
  • File Size: 190 KB
  • Pages: 8
  • Language: EN
  • Author: Malte Helmert and Gabriele Röger
  • Total Downloads: 65
  • Last Updated: 1 week ago

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