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A* Search Without Expansions: Learning Heuristic Functions with Deep Q-Networks
v1v2v3 (latest)

A* Search Without Expansions: Learning Heuristic Functions with Deep Q-Networks

8 February 2021
Forest Agostinelli
Alexander Shmakov
Alexander Shmakov
Stephen McAleer
Roy Fox
Pierre Baldi
ArXiv (abs)PDFHTMLGithub (193★)

Papers citing "A* Search Without Expansions: Learning Heuristic Functions with Deep Q-Networks"

10 / 10 papers shown
Quantum Compiling with Reinforcement Learning on a Superconducting
  Processor
Quantum Compiling with Reinforcement Learning on a Superconducting Processor
Z. T. Wang
Qiuhao Chen
Yuxuan Du
Z. H. Yang
Xiaoxia Cai
...
Huikai Xu
Yirong Jin
Ruixia Wang
Haifeng Yu
S. P. Zhao
277
11
0
18 Jun 2024
Reinforcement Learning from Diffusion Feedback: Q* for Image Search
Reinforcement Learning from Diffusion Feedback: Q* for Image Search
Aboli Rajan Marathe
VLM
255
0
0
27 Nov 2023
Learning Local Heuristics for Search-Based Navigation Planning
Learning Local Heuristics for Search-Based Navigation PlanningInternational Conference on Automated Planning and Scheduling (ICAPS), 2023
Rishi Veerapaneni
Muhammad Suhail Saleem
Maxim Likhachev
250
6
0
16 Mar 2023
ASP: Learn a Universal Neural Solver!
ASP: Learn a Universal Neural Solver!IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023
Chenguang Wang
Zhouliang Yu
Alexander Shmakov
Tianshu Yu
Yao-Chun Yang
AAML
275
40
0
01 Mar 2023
Graph Value Iteration
Graph Value Iteration
Dieqiao Feng
Daniel Schwalbe-Koda
B. Selman
152
0
0
20 Sep 2022
The (Un)Scalability of Heuristic Approximators for NP-Hard Search
  Problems
The (Un)Scalability of Heuristic Approximators for NP-Hard Search Problems
Sumedh Pendurkar
Taoan Huang
Sven Koenig
Guni Sharon
263
1
0
07 Sep 2022
Non-Blocking Batch A* (Technical Report)
Non-Blocking Batch A* (Technical Report)
Rishi Veerapaneni
Maxim Likhachev
315
1
0
15 Aug 2022
Efficient and practical quantum compiler towards multi-qubit systems
  with deep reinforcement learning
Efficient and practical quantum compiler towards multi-qubit systems with deep reinforcement learningQuantum Science and Technology (QST), 2022
Qiuhao Chen
Yuxuan Du
Qi Zhao
Yuliang Jiao
Xiliang Lu
Xingyao Wu
248
19
0
14 Apr 2022
Equivariant neural networks for recovery of Hadamard matrices
Equivariant neural networks for recovery of Hadamard matrices
A. Peres
E. Dias
Luís Sarmento
Hugo Penedones
163
0
0
31 Jan 2022
Exploiting Learned Policies in Focal Search
Exploiting Learned Policies in Focal SearchSymposium on Combinatorial Search (SoCS), 2021
Pablo Araneda
M. Greco
Jorge A. Baier
385
7
0
21 Apr 2021
1
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