Article

Adaptive A

Authors:

Sven Koenig,

Maxim LikhachevAuthors Info & Claims

AAMAS '05: Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems

Pages 1311 - 1312

https://doi.org/10.1145/1082473.1082748

Published: 25 July 2005 Publication History

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Abstract

Agents often have to perform repeated on-line searches as they gain additional knowledge about their environment. We describe an incremental version of A*, called Adaptive A*, that solves series of similar search problems faster than running A* repeatedly from scratch because it updates its heuristics between search episodes. It is simpler than other incremental versions of A* and thus likely easier to extend and adapt to new applications.

References

[1]

S. Koenig and M. Likhachev. D* Lite. In Proceedings of the National Conference on Artificial Intelligence, pages 476--483, 2002.

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[2]

S. Koenig, C. Tovey, and Y. Smirnov. Performance bounds for planning in unknown terrain. Artificial Intelligence, 147:253--279, 2003.

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Cited By

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Strub MGammell J(2022)Adaptively Informed Trees (AIT*) and Effort Informed Trees (EIT*)International Journal of Robotics Research10.1177/0278364921106957241:4(390-417)Online publication date: 1-Apr-2022
https://dl.acm.org/doi/10.1177/02783649211069572
Chong LJian LXueQuan L(2022) Static Rectangle Expansion A * Algorithm for Pathfinding IEEE Transactions on Games10.1109/TG.2020.301260214:1(23-35)Online publication date: Mar-2022
https://doi.org/10.1109/TG.2020.3012602
Chennoufi MBendella F(2020)Fuzzy controller and emotional model for evacuation of virtual crowd behaviorsIntelligent Decision Technologies10.3233/IDT-19009214:2(199-214)Online publication date: 1-May-2020
https://doi.org/10.3233/IDT-190092
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Index Terms

Adaptive A
1. Computing methodologies
  1. Artificial intelligence
    1. Search methodologies
      1. Discrete space search
      2. Game tree search

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Published In

AAMAS '05: Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems

July 2005

1407 pages

ISBN:1595930930

DOI:10.1145/1082473

Program Chairs:
Michal Pechoucek
Czech Republic
,
Donald Steiner
USA
,
Simon Thompson
UK

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 25 July 2005

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AAMAS05

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SIGAI

AAMAS05: AAMAS '05 - Fourth International Joint Conference on Autonomous Agents and Multiagent Systems 2005

July 25 - 29, 2005

The Netherlands

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Overall Acceptance Rate 1,155 of 5,036 submissions, 23%

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Cited By

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Strub MGammell J(2022)Adaptively Informed Trees (AIT*) and Effort Informed Trees (EIT*)International Journal of Robotics Research10.1177/0278364921106957241:4(390-417)Online publication date: 1-Apr-2022
https://dl.acm.org/doi/10.1177/02783649211069572
Chong LJian LXueQuan L(2022) Static Rectangle Expansion A * Algorithm for Pathfinding IEEE Transactions on Games10.1109/TG.2020.301260214:1(23-35)Online publication date: Mar-2022
https://doi.org/10.1109/TG.2020.3012602
Chennoufi MBendella F(2020)Fuzzy controller and emotional model for evacuation of virtual crowd behaviorsIntelligent Decision Technologies10.3233/IDT-19009214:2(199-214)Online publication date: 1-May-2020
https://doi.org/10.3233/IDT-190092
Strub MGammell J(2020)Adaptively Informed Trees (AIT*): Fast Asymptotically Optimal Path Planning through Adaptive Heuristics2020 IEEE International Conference on Robotics and Automation (ICRA)10.1109/ICRA40945.2020.9197338(3191-3198)Online publication date: May-2020
https://doi.org/10.1109/ICRA40945.2020.9197338
Schuster Dvan Zelst S(2020)Online Process Monitoring Using Incremental State-Space Expansion: An Exact AlgorithmBusiness Process Management10.1007/978-3-030-58666-9_9(147-164)Online publication date: 13-Sep-2020
https://dl.acm.org/doi/10.1007/978-3-030-58666-9_9
Ishida SRigter MHawes N(2019)Robot Path Planning for Multiple Target Regions2019 European Conference on Mobile Robots (ECMR)10.1109/ECMR.2019.8870971(1-6)Online publication date: Sep-2019
https://doi.org/10.1109/ECMR.2019.8870971
Przybylski MPutz B(2017)D* Extra Lite: A Dynamic A* With Search–Tree Cutting and Frontier–Gap RepairingInternational Journal of Applied Mathematics and Computer Science10.1515/amcs-2017-002027:2(273-290)Online publication date: 8-Jul-2017
https://doi.org/10.1515/amcs-2017-0020
Skrzypczyński P(2017)Path Planning for an Unmanned Ground Vehicle Traversing Rough Terrain with Unknown AreasAutomation 201710.1007/978-3-319-54042-9_29(319-329)Online publication date: 1-Mar-2017
https://doi.org/10.1007/978-3-319-54042-9_29
Baier JBotea AHarabor DHernandez C(2015)Fast Algorithm for Catching a Prey Quickly in Known and Partially Known Game MapsIEEE Transactions on Computational Intelligence and AI in Games10.1109/TCIAIG.2014.23378897:2(193-199)Online publication date: Jun-2015
https://doi.org/10.1109/TCIAIG.2014.2337889
Hernández CUras TKoenig SBaier JSun XMeseguer P(2015)Reusing cost-minimal paths for goal-directed navigation in partially known terrainsAutonomous Agents and Multi-Agent Systems10.1007/s10458-014-9266-029:5(850-895)Online publication date: 1-Sep-2015
https://dl.acm.org/doi/10.1007/s10458-014-9266-0
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Generalized Adaptive A*

Moving target D* Lite

Dynamic fringe-saving A*

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