0000000001294374

AUTHOR

Abdolreza Shirvani

showing 3 related works from this author

On enhancing the object migration automaton using the Pursuit paradigm

2017

Abstract One of the most difficult problems that is all-pervasive in computing is that of partitioning. It has applications in the partitioning of databases into relations, the realization of the relations themselves into sub-relations based on the partitioning of the attributes, the assignment of processes to processors, graph partitioning, and the task assignment problem, etc. The problem is known to be NP-hard. The benchmark solution for this for the Equi-Partitioning Problem (EPP) has involved the classic field of Learning Automata (LA), and the corresponding algorithm, the Object Migrating Automata (OMA) has been used in all of these application domains. While the OMA is a fixed struct…

Theoretical computer scienceGeneral Computer ScienceLearning automatabusiness.industryComputer scienceGraph partition020206 networking & telecommunications02 engineering and technologyObject (computer science)Field (computer science)Theoretical Computer ScienceAutomatonTask (computing)Modeling and Simulation0202 electrical engineering electronic engineering information engineeringBenchmark (computing)020201 artificial intelligence & image processingArtificial intelligencebusinessAssignment problem
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The Power of the “Pursuit” Learning Paradigm in the Partitioning of Data

2019

Traditional Learning Automata (LA) work with the understanding that the actions are chosen purely based on the “state” in which the machine is. This modus operandus completely ignores any estimation of the Random Environment’s (RE’s) (specified as \(\mathbb {E}\)) reward/penalty probabilities. To take these into consideration, Estimator/Pursuit LA utilize “cheap” estimates of the Environment’s reward probabilities to make them converge by an order of magnitude faster. This concept is quite simply the following: Inexpensive estimates of the reward probabilities can be used to rank the actions. Thereafter, when the action probability vector has to be updated, it is done not on the basis of th…

Mathematical optimizationTheoretical computer scienceLearning automataBasis (linear algebra)Computer scienceRank (computer programming)Object PartitioningPartitioning-based learningEstimatorLearning Automata02 engineering and technologyProbability vectorField (computer science)AutomatonRanking0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processing[INFO]Computer Science [cs]Object Migration Automaton
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On Invoking Transitivity to Enhance the Pursuit-Oriented Object Migration Automata

2018

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