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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
Destructiveness of Lexicographic Parsimony Pressure and Alleviation by a Concatenation Crossover in Genetic Programming
For theoretical analyses there are two specifics distinguishing GP from many other areas of evolutionary computation. First, the… 
2016
2016
Parallel space saving on multi‐ and many‐core processors
Given an array A of n elements and a value 2≤k≤n, a frequent item or k‐majority element is an element occurring in A more than n… 
2011
2011
The Distributed Multiple Voting Problem
A networked set of agents holding binary opinions does not seem to be able to compute its majority opinion by means of local… 
2011
2011
Finding frequent items in parallel
We present a deterministic parallel algorithm for the k‐majority problem, that can be used to find in parallel frequent items, i… 
2006
2006
The best currently known class of dynamically equivalent cellular automata rules for density classification
2006
2006
An Analytical Formulation for Cellular Automata (CA) Based Solution of Density Classification Task (DCT)
This paper presents an analytical solution for Density Classification Task (DCT) with an n cell inhomogeneous Cellular Automata… 
Highly Cited
2001
Highly Cited
2001
Pareto Optimality in Coevolutionary Learning
We develop a novel coevolutionary algorithm based upon the concept of Pareto optimality. The Pareto criterion is core to… 
Highly Cited
1997
Highly Cited
1997
Coevolving Cellular Automata: Be Aware of the Red Queen!
This paper studies the use of coevolution to search for a cellular automaton (CA) solving the well-known density classification… 
Highly Cited
1994
Highly Cited
1994
A Genetic Algorithm Discovers Particle-Based Computation in Cellular Automata
How does evolution produce sophisticated emergent computation in systems composed of simple components limited to local… 
Highly Cited
1989
Highly Cited
1989
Generalization and Scaling in Reinforcement Learning
In associative reinforcement learning, an environment generates input vectors, a learning system generates possible output… 
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