Investigation of Replicating Tiles in Cellular Automata Designed by Evolution Using Conditionally Matching Rules

Investigation of Replicating Tiles in Cellular Automata Designed by Evolution Using Conditionally Matching Rules

Paper in proceedings (conference paper)

In this paper we investigate the evolutionary design of replicating tiles in cellular automata. In particular, various sizes of the tiles will be considered whose replication ought to be performed by satisfying a given arrangement of the tiles with respect to each other. The goal is to determine the abilities of the genetic algorithm in combination with conditionally matching rules used for representing the transition functions of cellular automata to find solutions for tiles consisting of up to a hundred of cells. A comparative study will be presented considering the success rate, computational effort and complexity of the obtained solutions as the main values of interest. It will be shown that, in addition to the tile size and the number of states of the cellular automaton, the probability of finding a correct solution is also substantially influenced by the arrangement style. The results show that the tile arrangement that may be considered as the simplest one does not have to necessarily be easily realisable by the genetic algorithm as a transition function for a cellular automaton.

In this paper we investigate the evolutionary design of replicating tiles in cellular automata. In particular, various sizes of the tiles will be considered whose replication ought to be performed by satisfying a given arrangement of the tiles with respect to each other. The goal is to determine the abilities of the genetic algorithm in combination with conditionally matching rules used for representing the transition functions of cellular automata to find solutions for tiles consisting of up to a hundred of cells. A comparative study will be presented considering the success rate, computational effort and complexity of the obtained solutions as the main values of interest. It will be shown that, in addition to the tile size and the number of states of the cellular automaton, the probability of finding a correct solution is also substantially influenced by the arrangement style. The results show that the tile arrangement that may be considered as the simplest one does not have to necessarily be easily realisable by the genetic algorithm as a transition function for a cellular automaton.

cellular automaton; genetic algorithm; transition function; conditionally matching rule; replication

cellular automaton; genetic algorithm; transition function; conditionally matching rule; replication

BIDLO, M.

2016

07.12.2015

IEEE Computational Intelligence Society

Cape Town

978-1-4799-7560-0

2015 IEEE International Conference on Evolvable Systems (ICES)

Proceedings of the 2015 IEEE Symposium Series on Computational Intelligence (SSCI)

1506

1513

8

http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7376789

ices2015