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Improved Anytime D* Algorithm

Chapter
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 247)

Abstract

In the dynamic domain, agents often operate in the terrain which is only incompletely known and can be dynamically updated on the fly. In this case, dynamic navigation algorithm, which is required to find out an optimal solution to its goal, has been an important component in planning. However, under the environments where time is more critical than optimality, a sub-optimal solution is required. Therefore the challenge for practical applications is to find a high sub-optimal solution in limited time. The dynamic algorithm Anytime D*(AD*) is currently the best anytime algorithm which aims to return a high sub-optimal solution with short corresponding time and control of sub-optimality. In this chapter, a new algorithm named Improved Anytime D*(IAD*) is introduced. By reducing the search space, experiment results show IAD* better outperforms Anytime D* in various random benchmarks.

Keywords

Anytime algorithm Artificial intelligence D* lite Incremental algorithm Navigation algorithm Planning 

Notes

Acknowledgments

This work was supported by University Research Council’s (URC), 2012 Summer Graduate Student Research Fellowships funded by University of Cincinnati.

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Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  1. 1.Department of Computer ScienceUniversity of CincinnatiCincinnatiUSA
  2. 2.Institute of Information EngneeringChinese Academy of ScienceBeijingChina

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