Improving HLRTA

Carlos Hernández, Pedro Meseguer

Resultado de la investigación: Conference contribution

1 Cita (Scopus)

Resumen

Real-time search methods allow an agent to move in unknown environments. We provide two enhancements to the real-time search algorithm HLRTA*(k). First, we give a better way to perform bounded propagation, generating the HLRTA*LS(k) algorithm. Second, we consider the option of doing more than one action per planning step, by analyzing the quality of the heuristic found during lookahead, producing the HLRTA*(k, d) algorithm. We provide experimental evidence of the benefits of both algorithms, with respect to other real-time algorithms on existing benchmarks.

Idioma originalEnglish
Título de la publicación alojadaCurrent Topics in Artificial Intelligence - 12th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2007
Páginas110-119
Número de páginas10
Volumen4788 LNAI
EstadoPublished - 2007
Evento12th Conference of the Spanish Association for Artificial Intelligence and its associated Conference on Technology Transfer on Artificial Intelligence, CAEPIA/TTIA 2007 - Salamanca, Spain
Duración: 12 nov 200716 nov 2007

Serie de la publicación

NombreLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volumen4788 LNAI
ISSN (versión impresa)03029743
ISSN (versión digital)16113349

Other

Other12th Conference of the Spanish Association for Artificial Intelligence and its associated Conference on Technology Transfer on Artificial Intelligence, CAEPIA/TTIA 2007
PaísSpain
CiudadSalamanca
Período12/11/0716/11/07

Huella dactilar

Real-time
Look-ahead
Search Methods
Search Algorithm
Enhancement
Planning
Heuristics
Propagation
Benchmark
Unknown
Evidence

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Citar esto

Hernández, C., & Meseguer, P. (2007). Improving HLRTA. En Current Topics in Artificial Intelligence - 12th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2007 (Vol. 4788 LNAI, pp. 110-119). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4788 LNAI).
Hernández, Carlos ; Meseguer, Pedro. / Improving HLRTA. Current Topics in Artificial Intelligence - 12th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2007. Vol. 4788 LNAI 2007. pp. 110-119 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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title = "Improving HLRTA",
abstract = "Real-time search methods allow an agent to move in unknown environments. We provide two enhancements to the real-time search algorithm HLRTA*(k). First, we give a better way to perform bounded propagation, generating the HLRTA*LS(k) algorithm. Second, we consider the option of doing more than one action per planning step, by analyzing the quality of the heuristic found during lookahead, producing the HLRTA*(k, d) algorithm. We provide experimental evidence of the benefits of both algorithms, with respect to other real-time algorithms on existing benchmarks.",
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Hernández, C & Meseguer, P 2007, Improving HLRTA. En Current Topics in Artificial Intelligence - 12th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2007. vol. 4788 LNAI, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 4788 LNAI, pp. 110-119, 12th Conference of the Spanish Association for Artificial Intelligence and its associated Conference on Technology Transfer on Artificial Intelligence, CAEPIA/TTIA 2007, Salamanca, Spain, 12/11/07.

Improving HLRTA. / Hernández, Carlos; Meseguer, Pedro.

Current Topics in Artificial Intelligence - 12th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2007. Vol. 4788 LNAI 2007. p. 110-119 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4788 LNAI).

Resultado de la investigación: Conference contribution

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AB - Real-time search methods allow an agent to move in unknown environments. We provide two enhancements to the real-time search algorithm HLRTA*(k). First, we give a better way to perform bounded propagation, generating the HLRTA*LS(k) algorithm. Second, we consider the option of doing more than one action per planning step, by analyzing the quality of the heuristic found during lookahead, producing the HLRTA*(k, d) algorithm. We provide experimental evidence of the benefits of both algorithms, with respect to other real-time algorithms on existing benchmarks.

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Hernández C, Meseguer P. Improving HLRTA. En Current Topics in Artificial Intelligence - 12th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2007. Vol. 4788 LNAI. 2007. p. 110-119. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).