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.
Supported by the Spanish REPLI-III project TIC-2006-15387-C03-01.
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Hernández, C., Meseguer, P. (2007). Improving HLRTA*(k). In: Borrajo, D., Castillo, L., Corchado, J.M. (eds) Current Topics in Artificial Intelligence. CAEPIA 2007. Lecture Notes in Computer Science(), vol 4788. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75271-4_12
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DOI: https://doi.org/10.1007/978-3-540-75271-4_12
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