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Best-First Heuristic Search for Multicore Machines

E. Burns, S. Lemons, W. Ruml, R. Zhou
2010 The Journal of Artificial Intelligence Research  
Our approach is general, allowing it to extend easily to suboptimal and anytime heuristic search.  ...  In an empirical comparison on STRIPS planning, grid pathfinding, and sliding tile puzzle problems using 8-core machines, we show that A*, weighted A* and Anytime weighted A* implemented using PBNF yield  ...  Some of these results were previously reported by Burns, Lemons, Zhou, and Ruml (2009b) and Burns, Lemons, Ruml, and Zhou (2009a) .  ... 
doi:10.1613/jair.3094 fatcat:lp4x2vgfs5dxnay47jbbkdbfba

MAA*: A Heuristic Search Algorithm for Solving Decentralized POMDPs [article]

Daniel Szer, Francois Charpillet, Shlomo Zilberstein
2012 arXiv   pre-print
Our solution is based on a synthesis of classical heuristic search and decentralized control theory. Experimental results show that MAA* has significant advantages.  ...  We present multi-agent A* (MAA*), the first complete and optimal heuristic search algorithm for solving decentralized partially-observable Markov decision problems (DEC-POMDPs) with finite horizon.  ...  Acknowledgments We thank Daniel Bernstein and Bruno Scherrer for helpful discussions on this work.  ... 
arXiv:1207.1359v1 fatcat:qlhernresjc7hoy77gwctnyneq

Anytime Multi-Agent Path Finding via Machine Learning-Guided Large Neighborhood Search

Taoan Huang, Jiaoyang Li, Sven Koenig, Bistra Dilkina
2022 PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE  
Anytime algorithms find solutions quickly for large instances and then improve them to close-to-optimal ones over time.  ...  Search (LNS).  ...  The views and conclusions contained in this document are those of the authors and should not be interpreted as necessarily representing the official policies, either expressed or implied, of NSF or the  ... 
doi:10.1609/aaai.v36i9.21168 fatcat:th562mpwe5gm7aign3o4zrzl4m

Research Challenges in Combinatorial Search

Richard Korf
2021 PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE  
more realistic problem domains, analyzing the time complexity of heuristic search algorithms, and capitalizing on advances in computing hardware, such as very large external memories and multi-core processors  ...  These include solving and playing games with chance, hidden information, and multiple players, optimally solving larger instances of well-known single-agent toy problems, applying search techniques to  ...  Thanks to Victoria Cortessis for helpful comments on a draft of this paper.  ... 
doi:10.1609/aaai.v26i1.8444 fatcat:dteytrpj75f6jcaeqbevj4wt5m

Versatile Verification of Tree Ensembles [article]

Laurens Devos, Wannes Meert, Jesse Davis
2020 arXiv   pre-print
First, it provides anytime lower and upper bounds when the optimization problem cannot be solved exactly.  ...  Veritas formulates the verification task as a generic optimization problem and introduces a novel search space representation. Veritas offers two key advantages.  ...  We propose a novel search space for which an admissible heuristic exists, which confers two advantages. First, it provides anytime upper and lower bounds.  ... 
arXiv:2010.13880v1 fatcat:vvdglqfalbhtlpnqgovaf7ux2m

Vulcan: A Monte Carlo Algorithm for Large Chance Constrained MDPs with Risk Bounding Functions [article]

Benjamin J Ayton, Brian C Williams
2018 arXiv   pre-print
and returning solutions with a mean suboptimality on the order of a few percent.  ...  We show that Vulcan and its variants run tens to hundreds of times faster than linear programming methods, and over ten times faster than heuristic based methods, all without the need for a heuristic,  ...  Acknowledgements The authors would like to acknowledge and thank the Exxon Mobil Corporation for their financial support (grant EM09079).  ... 
arXiv:1809.01220v1 fatcat:zdliv7d2c5ghjghvganzzbwyfy

Graph-Based Multi-Robot Path Finding and Planning

Hang Ma
2022 Current Robotics Reports  
Purpose of Review Planning collision-free paths for multiple robots is important for real-world multi-robot systems and has been studied as an optimization problem on graphs, called Multi-Agent Path Finding  ...  Summary Algorithmic techniques for MAPF problems have addressed important aspects of several multi-robot applications, including automated warehouse fulfillment and sortation, automated train scheduling  ...  Acknowledgment This work was supported by the Natural Sciences and Engineering Research Council (NSERC) of Canada under grant number RGPIN2020-06540.  ... 
doi:10.1007/s43154-022-00083-8 fatcat:o27tkjtzpnd7zibpnhgcabs6oy

Variable Neighborhood Search for Graphical Model Energy Minimization

Abdelkader Ouali, David Allouche, Simon de Givry, Samir Loudni, Yahia Lebbah, Lakhdar Loukil, Patrice Boizumault
2019 Artificial Intelligence  
Most complete methods rely on tree search, while incomplete methods rely on local search. Among them, we study Variable Neighborhood Search (VNS) for graphical models.  ...  We further propose a parallel version of our method improving its anytime behavior on difficult instances coming from a large graphical model benchmark.  ...  We are grateful to the genotoul bioinformatics platform Toulouse Midi-Pyrenees (Bioinfo Genotoul) and the high performance center of Cerist-Algiers in Algeria for providing computing and storage resources  ... 
doi:10.1016/j.artint.2019.103194 fatcat:6cf6f3gvfvfhjlm4ve7zbjqbme

Algorithms for Graph-Constrained Coalition Formation in the Real World [article]

Filippo Bistaffa, Alessandro Farinelli, Jesús Cerquides, Juan A. Rodríguez-Aguilar, Sarvapali D. Ramchurn
2016 arXiv   pre-print
a 12-core machine.  ...  We benchmark CFSS on both synthetic and realistic scenarios, using a real-world dataset consisting of the energy consumption of a large number of households in the UK.  ...  ACKNOWLEDGMENTS COR (TIN 2012-38876-C02-01) , Collectiveware TIN 2015-66863-C2-1-R (MINECO/FEDER), and the Generalitat of Catalunya 2014-SGR-118 funded Cerquides and Rodríguez-Aguilar.  ... 
arXiv:1612.04299v1 fatcat:mobedrraenagdhh22rm5clyipq

Anytime Capacity Expansion in Medical Residency Match by Monte Carlo Tree Search [article]

Kenshi Abe, Junpei Komiyama, Atsushi Iwasaki
2022 arXiv   pre-print
To tackle the problem, we propose an anytime method that the upper confidence tree searches the space of capacity expansions, each of which has a resident-optimal stable assignment that the deferred acceptance  ...  Constructing a good search tree representation significantly boosts the performance of the proposed method.  ...  UCT can be viewed as a combination of multi-armed bandit algorithm and monte-carlo search. C Proof of Theorem 5 Proof. Let N = N − 1.  ... 
arXiv:2202.06570v2 fatcat:xzvx6eygqngh7po74dcfhxwply

Continuing Plan Quality Optimisation

Fazlul Hasan Siddiqui, Patrik Haslum
2015 The Journal of Artificial Intelligence Research  
BDPO2 can be seen as an application of the large neighbourhood search (LNS) local search strategy to planning, where the neighbourhood of a plan is defined by replacing one or more subplans with improved  ...  On-line learning is also used to adapt the strategy for selecting subplans and subplanners over the course of plan optimisation.  ...  Anytime search tries to strike a balance between optimal (or bounded suboptimal) and greedy heuristic search methods.  ... 
doi:10.1613/jair.4980 fatcat:dgtziugfmnd3xbrdpyr4ix2sde

MurTree: Optimal Decision Trees via Dynamic Programming and Search

Emir Demirovic, Anna Lukina, Emmanuel Hebrard, Jeffrey Chan, James Bailey, Christopher Leckie, Kotagiri Ramamohanarao, Peter J. Stuckey
2022 Journal of machine learning research  
We follow this line of work and provide a novel algorithm for learning optimal classification trees based on dynamic programming and search.  ...  Our algorithm supports constraints on the depth of the tree and number of nodes.  ...  An anonymous reviewer motivated us to explore caching based on datasets which led to improvements.  ... 
dblp:journals/jmlr/DemirovicLHCBLR22 fatcat:dcq53h25n5dazo6pyehzqsibwi

Parallel Data Mining Revisited. Better, Not Faster [chapter]

Zaenal Akbar, Violeta N. Ivanova, Michael R. Berthold
2012 Lecture Notes in Computer Science  
In this paper we argue that parallel and/or distributed compute resources can be used differently: instead of focusing on speeding up algorithms, we propose to focus on improving accuracy.  ...  We discuss a number of generic ways of tuning data mining algorithms and elaborate on two prominent examples in more detail.  ...  In this paper, we argue that modern architectures, which provide access to numerous parallel computing resources, emphasized by the recent advance of multi-core architectures, can also be utilized to reduce  ... 
doi:10.1007/978-3-642-34156-4_4 fatcat:w7c5wqlbnbeubly2ouflazfhee

Parallel data mining revisited: Better, not faster

Michael R. Berthold
2012 2012 IEEE 16th International Conference on Intelligent Engineering Systems (INES)  
In this paper we argue that parallel and/or distributed compute resources can be used differently: instead of focusing on speeding up algorithms, we propose to focus on improving accuracy.  ...  We discuss a number of generic ways of tuning data mining algorithms and elaborate on two prominent examples in more detail.  ...  In this paper, we argue that modern architectures, which provide access to numerous parallel computing resources, emphasized by the recent advance of multi-core architectures, can also be utilized to reduce  ... 
doi:10.1109/ines.2012.6249824 fatcat:f3yf2dz27ndoljud3bp2gei2f4

MurTree: Optimal Classification Trees via Dynamic Programming and Search [article]

Emir Demirović, Anna Lukina, Emmanuel Hebrard, Jeffrey Chan, James Bailey, Christopher Leckie, Kotagiri Ramamohanarao, Peter J. Stuckey
2022 arXiv   pre-print
We follow this line of work and provide a novel algorithm for learning optimal classification trees based on dynamic programming and search.  ...  Our algorithm supports constraints on the depth of the tree and number of nodes.  ...  An anonymous reviewer motivated us to explore caching based on datasets which led to improvements.  ... 
arXiv:2007.12652v4 fatcat:vaou77wq6rb3hfvaijkmbj7dea
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