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Proceedings ArticleDOI

Autonomous parallel heuristic combinatorial search

C.-C. Wang, +1 more
- pp 741-746
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TLDR
A theoretical analysis of a new autonomous parallel heuristic search algorithm that shares information that monitors the progress of the search and uses consensus to limit the amount of time spent in expanding nodes that are not on the optimal path.
Abstract
Heuristic search is the process of searching a state space under the guidance of an evaluation function. Most research on parallelizing heuristic search algorithms has emphasized system problems such as load balancing and reduction in memory use. A theoretical analysis of a new autonomous parallel heuristic search algorithm is introduced. Rather than simply dividing the search space among the processors, the processors share information that monitors the progress of the search and use consensus to limit the amount of time spent in expanding nodes that are not on the optimal path. Each processor uses a different admissible heuristic function, and it is shown that the expected number of nodes generated by each processor in the course of the search is reduced by a factor that reflects the consensus among the processors. The asynchronous behavior of the algorithm eliminates synchronization delays. >

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Citations
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Patent

System for parallel implementation of combinatorial optimization in a multiprocessor network for generating search graphs for solving enumerative problems

TL;DR: In this article, the shadow nodes are used to refine solutions for enumerative problems, search graph and the like while providing a near 100% utilization of a processor time in a multiprocessor network.
References
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Book

Principles of Artificial Intelligence

TL;DR: This classic introduction to artificial intelligence describes fundamental AI ideas that underlie applications such as natural language processing, automatic programming, robotics, machine vision, automatic theorem proving, and intelligent data retrieval.
Journal ArticleDOI

Depth-first iterative-deepening: an optimal admissible tree search

TL;DR: This heuristic depth-first iterative-deepening algorithm is the only known algorithm that is capable of finding optimal solutions to randomly generated instances of the Fifteen Puzzle within practical resource limits.
Book ChapterDOI

Chess 4.5-The Northwestern University chess program

TL;DR: This chapter will describe the structure of the CHESS 4.5 program, focusing on the practical considerations that motivated the implementation of its various features.

The design and analysis of algorithms for asynchronous multiprocessors.

TL;DR: This thesis demonstrates that asynchronous multiprocessors can be used efficiently in different problem domains, provided that appropriate algorithms are used and presents an algorithm to illustrate that the fluctuations are not always a negative factor but can also be utilized advantageously.
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