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Left Heavy Tails and the Effectiveness of the Policy and Value Networks
  in DNN-based best-first search for Sokoban Planning

Left Heavy Tails and the Effectiveness of the Policy and Value Networks in DNN-based best-first search for Sokoban Planning

28 June 2022
Dieqiao Feng
Carla P. Gomes
B. Selman
ArXivPDFHTML

Papers citing "Left Heavy Tails and the Effectiveness of the Policy and Value Networks in DNN-based best-first search for Sokoban Planning"

8 / 8 papers shown
Title
What Matters in Hierarchical Search for Combinatorial Reasoning Problems?
What Matters in Hierarchical Search for Combinatorial Reasoning Problems?
Michał Zawalski
Gracjan Góral
Michał Tyrolski
Emilia Wisnios
Franciszek Budrowski
Marek Cygan
Łukasz Kuciński
Piotr Miłoś
68
0
0
05 Jun 2024
Solving Sokoban with forward-backward reinforcement learning
Solving Sokoban with forward-backward reinforcement learning
Yaron Shoham
G. Elidan
OffRL
89
6
0
05 May 2021
Policy-Guided Heuristic Search with Guarantees
Policy-Guided Heuristic Search with Guarantees
Laurent Orseau
Levi H. S. Lelis
59
28
0
21 Mar 2021
Solving Hard AI Planning Instances Using Curriculum-Driven Deep
  Reinforcement Learning
Solving Hard AI Planning Instances Using Curriculum-Driven Deep Reinforcement Learning
Dieqiao Feng
Carla P. Gomes
B. Selman
LRM
28
23
0
04 Jun 2020
Predictive Uncertainty Estimation via Prior Networks
Predictive Uncertainty Estimation via Prior Networks
A. Malinin
Mark Gales
UD
BDL
EDL
UQCV
PER
186
920
0
28 Feb 2018
Mastering Chess and Shogi by Self-Play with a General Reinforcement
  Learning Algorithm
Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm
David Silver
Thomas Hubert
Julian Schrittwieser
Ioannis Antonoglou
Matthew Lai
...
D. Kumaran
T. Graepel
Timothy Lillicrap
Karen Simonyan
Demis Hassabis
141
1,775
0
05 Dec 2017
Snapshot Ensembles: Train 1, get M for free
Snapshot Ensembles: Train 1, get M for free
Gao Huang
Yixuan Li
Geoff Pleiss
Zhuang Liu
John E. Hopcroft
Kilian Q. Weinberger
OOD
FedML
UQCV
125
950
0
01 Apr 2017
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
821
9,318
0
06 Jun 2015
1