High-throughput implementation of tree-search algorithms for vector precoding

AbstractTerraces in phylogenetic tree space are, among other things, important for the design of tree space search strategies. While the phenomenon of phylogenetic terraces is already known for unlinked partition models on partitioned phylogenomic data sets, it has not yet been studied if an analogous structure is present under linked and scaled partition models. To this end, we analyze aspects such as the log-likelihood distributions, likelihood-based significance tests, and nearest neighborhood interchanges on the trees residing on a terrace and compare their distributions among unlinked, linked, and scaled partition models. Our study shows that there exists a terrace-like structure under linked and scaled partition models as well. We denote this phenomenon as quasi-terrace. Therefore quasi-terraces should be taken into account in the design of tree search algorithms as well as when reporting results on ‘the’ final tree topology in empirical phylogenetic studies.

Download Full-text

Open Loop Execution of Tree-Search Algorithms

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence ◽

10.24963/ijcai.2018/327 ◽

2018 ◽

Cited By ~ 1

Author(s):

Erwan Lecarpentier ◽

Guillaume Infantes ◽

Charles Lesire ◽

Emmanuel Rachelson

Keyword(s):

Search Algorithms ◽

Open Loop ◽

Tree Search ◽

Open Loop Control ◽

Time Step ◽

Line Planning ◽

Loop Control ◽

Stochastic Planning ◽

On Line ◽

Planning Algorithms

In the context of tree-search stochastic planning algorithms where a generative model is available, we consider on-line planning algorithms building trees in order to recommend an action. We investigate the question of avoiding re-planning in subsequent decision steps by directly using sub-trees as action recommender. Firstly, we propose a method for open loop control via a new algorithm taking the decision of re-planning or not at each time step based on an analysis of the statistics of the sub-tree. Secondly, we show that the probability of selecting a suboptimal action at any depth of the tree can be upper bounded and converges towards zero. Moreover, this upper bound decays in a logarithmic way between subsequent depths. This leads to a distinction between node-wise optimality and state-wise optimality. Finally, we empirically demonstrate that our method achieves a compromise between loss of performance and computational gain.

Download Full-text

Optical Techniques For Increasing The Efficiency Of Tree Search Algorithms

10.1117/12.947925 ◽

1989 ◽

Author(s):

Michael W. Haney ◽

Ravindra A. Athale

Keyword(s):

Search Algorithms ◽

Tree Search ◽

Optical Techniques

Download Full-text

Tree-Search Algorithms

Graph Theory - Graduate Texts in Mathematics ◽

10.1007/978-1-84628-970-5_6 ◽

2008 ◽

pp. 135-156

Keyword(s):

Search Algorithms ◽

Tree Search

Download Full-text

Tree search algorithms for self-adaptive maximum-likelihood sequence estimation

Proceedings of 1995 IEEE International Symposium on Information Theory ◽

10.1109/isit.1995.550392 ◽

2002 ◽

Author(s):

B.-P. Paris ◽

A.R. Shah

Keyword(s):

Maximum Likelihood ◽

Search Algorithms ◽

Tree Search ◽

Sequence Estimation ◽

Maximum Likelihood Sequence Estimation ◽

Self Adaptive

Download Full-text

TrapAB: A New Position Search Algorithm in Chinese Chess Computer Game

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.380-384.1621 ◽

2013 ◽

Vol 380-384 ◽

pp. 1621-1624 ◽

Cited By ~ 1

Author(s):

Jian Fang ◽

Jian Chi ◽

Hong Yi Jian

Keyword(s):

Search Algorithm ◽

Computer Game ◽

Search Algorithms ◽

Tree Search ◽

Game Playing ◽

Game Tree ◽

Alpha Beta ◽

Comparative Results ◽

Potential Traps ◽

Game Tree Search

In this paper, we propose an improved alpha-beta search algorithm, named trappy alpha-beta (simply), for game-tree in order to identify and set the potential traps in the game playing. can be regarded as an extension of the traditional alpha-beta search algorithm which ties to predict when the opponent might make a mistake and select such moves that can most likely lead the an opponent into the trap by comparing the various scores returned through iterative deepening technology. In our experiment, we test the performance of in comparison with three game-tree search algorithms, i.e., min-max, trappy minimax, and alpha-beta, by playing with four testing opponents, which are obtained form a typical Chinese chess computer game program-Xqwizard (http://www.xqbase.com). The comparative results show that our designedcan effectively find and set the traps in the playing with opponents.

Download Full-text