LRTA*(k)

  • Authors:

  • Carlos Hernández;Pedro Meseguer

  • Affiliations:

  • Institut d'Investigació en Intelligència Artificial, CSIC, Bellaterra, Spain;Institut d'Investigació en Intelligència Artificial, CSIC, Bellaterra, Spain

  • Venue:
  • IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
  • Year:
  • 2005

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Abstract

LRTA* is a real-time heuristic search algorithm widely used. In each iteration it updates the heuristic estimate of the current state. Here we present LRTA*(k), a new LRTA*-based algorithm that is able to update the heuristic estimates of up to k states, not necessarily distinct. Based on bounded propagation, this updating strategy maintains heuristic admissibility, so the new algorithm keeps the good theoretical properties of LRTA*. Experimentally, we show that LRTA*(k) produces better solutions in the first trial and converges faster when compared with other state-of-the-art algorithms on benchmarks for real-time search.