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Local Search for Planning and Scheduling [electronic resource] : ECAI 2000 Workshop, Berlin, Germany, August 21, 2000. Revised Papers /

Contributor(s): Material type: TextTextSeries: Lecture Notes in Artificial Intelligence ; 2148Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2001Edition: 1st ed. 2001Description: VIII, 176 p. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783540456124
Subject(s): Additional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification:
  • 006.3 23
LOC classification:
  • Q334-342
  • TA347.A78
Online resources:
Contents:
Invited Paper -- Meta-heuristics: The State of the Art -- Combinatorial Optimization -- Solving the Sports League Scheduling Problem with Tabu Search -- Lagrange Multipliers for Local Search on Planning Graphs -- Planning with Resources -- Beyond the Plan-Length Criterion -- An Empirical Evaluation of the Effectiveness of Local Search for Replanning -- Board-Laying Techniques Improve Local Search in Mixed Planning and Scheduling -- Empirical Evaluation of Local Search Methods for Adapting Planning Policies in a Stochastic Environment -- Related Approaches -- The GRT Planner: New Results -- Incremental Local Search for Planning Problems -- Map Drawing Based on a Resource-Constrained Search for a Navigation System.
In: Springer Nature eBook
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Invited Paper -- Meta-heuristics: The State of the Art -- Combinatorial Optimization -- Solving the Sports League Scheduling Problem with Tabu Search -- Lagrange Multipliers for Local Search on Planning Graphs -- Planning with Resources -- Beyond the Plan-Length Criterion -- An Empirical Evaluation of the Effectiveness of Local Search for Replanning -- Board-Laying Techniques Improve Local Search in Mixed Planning and Scheduling -- Empirical Evaluation of Local Search Methods for Adapting Planning Policies in a Stochastic Environment -- Related Approaches -- The GRT Planner: New Results -- Incremental Local Search for Planning Problems -- Map Drawing Based on a Resource-Constrained Search for a Navigation System.

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