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Majority problem (cellular automaton)

Known as: Density classification task, GKL Majority 
The majority problem, or density classification task is the problem of finding one-dimensional cellular automaton rules that accurately perform… 
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Related topics

Related topics

9 relations
Boyer–Moore majority vote algorithmCellular automatonDeterministic algorithmGenetic algorithm

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2018
2018
A Proof of a Heavy Hitters Algorithm
This note is meant to teach program development and formal proof in an introductory computer science course. Given a bag of items… 
2013
2013
WEIGHTED MAJORITY RULE FOR HYBRID CELLULAR AUTOMATA TOPOLOGY AND NEIGHBORHOOD
Evolution rules for Cellular Automata (CAs) able to perform computational tasks which require global coordination highlight an… 
2012
2012
Dynamics of Networks Evolved for Cellular Automata Computation
Cellular Automata (CAs) represent useful and important tools in the study of complex systems and interactions. The problem of… 
2011
2011
Genetic Algorithm for the solution of majority problem
Many natural and social systems exhibit globally organized behavior without the aid of a centralized control. Examples of such… 
2006
2006
The best currently known class of dynamically equivalent cellular automata rules for density classification
2004
2004
Variants of the majority problem
2004
2004
Evolving Transition Rules for Multi Dimensional Cellular Automata
Genetic Algorithms have been used before to evolve transition rules for one dimensional Cellular Automata (CA) to solve e.g. the… 
2003
2003
Two-dimensional cellular automata of radius one for density classification task p=1/2
2002
2002
Discovery of the Boolean Functions to the Best Density-Classification Rules Using Gene Expression Programming
Cellular automata are idealized versions of massively parallel, decentralized computing systems capable of emergent behaviors… 
1995
1995
Hierarchical mixture of experts and Max-Min propagation neural networks
The max-min propagation neural network model is considered as a hierarchical mixture of experts by replacing the max (min) units… 
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