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  1. Truncated incremental search.Sandip Aine & Maxim Likhachev - 2016 - Artificial Intelligence 234 (C):49-77.
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  • Potential-based bounded-cost search and Anytime Non-Parametric A ⁎.Roni Stern, Ariel Felner, Jur van den Berg, Rami Puzis, Rajat Shah & Ken Goldberg - 2014 - Artificial Intelligence 214 (C):1-25.
  • Probably bounded suboptimal heuristic search.Roni Stern, Gal Dreiman & Richard Valenzano - 2019 - Artificial Intelligence 267 (C):39-57.
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  • Controlling the learning process of real-time heuristic search.Masashi Shimbo & Toru Ishida - 2003 - Artificial Intelligence 146 (1):1-41.
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  • Incorporating weights into real-time heuristic search.Nicolás Rivera, Jorge A. Baier & Carlos Hernández - 2015 - Artificial Intelligence 225 (C):1-23.
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  • A heuristic search algorithm with modifiable estimate.László Mérõ - 1984 - Artificial Intelligence 23 (1):13-27.
  • Linear-space best-first search.Richard E. Korf - 1993 - Artificial Intelligence 62 (1):41-78.
  • Job sequencing with one common and multiple secondary resources: An A⁎/Beam Search based anytime algorithm.Matthias Horn, Günther Raidl & Christian Blum - 2019 - Artificial Intelligence 277 (C):103173.
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  • Speeding up problem solving by abstraction: a graph oriented approach.R. C. Holte, T. Mkadmi, R. M. Zimmer & A. J. MacDonald - 1996 - Artificial Intelligence 85 (1-2):321-361.
  • A stochastic process approach for multi-agent path finding with non-asymptotic performance guarantees.Xiaoyu He, Xueyan Tang, Wentong Cai & Jingning Li - 2024 - Artificial Intelligence 329 (C):104084.
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  • The heuristic search under conditions of error.Larry R. Harris - 1974 - Artificial Intelligence 5 (3):217-234.
  • WeightedA∗search – unifying view and application.Rüdiger Ebendt & Rolf Drechsler - 2009 - Artificial Intelligence 173 (14):1310-1342.
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  • Distributed extended beam search for quantitative model checking.Anton J. Wijs & Bert Lisser - 2007 - In A. Lomuscio & S. Edelkamp (eds.), Model Checking and Artificial Intelligence. Springer. pp. 166--184.