Design, observation, surprise! A test of emergence
Artificial Life
Ansatz for dynamical hierarchies
Artificial Life
Toward a formalization of emergence
Artificial Life
GECCO '96 Proceedings of the 1st annual conference on Genetic and evolutionary computation
How an optimal observer can collapse the search space
Proceedings of the 8th annual conference on Genetic and evolutionary computation
A gestalt genetic algorithm: less details for better search
Proceedings of the 9th annual conference on Genetic and evolutionary computation
The Gestalt heuristic: emerging abstraction to improve combinatorial search
Natural Computing: an international journal
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This paper elaborates upon an idea and a development introduced and presented by Bersini in [1]. Roughly, by observing the search space of a combinatorial problem in a “clever” way, it can be drastically reduced. In order to discover this “clever way”, a second search process has to be engaged in the space of the observables. So two Genetic Algorithms (GAs) are intertwined to solve the whole problem: one in the original space and one in the space of observables of the original one. We are going to present and evaluate this idea on a Cellular Automata (CA) implementation of a binary numbers adder. The experiments show that the new algorithm, combining the two evolutionary searches, speeds up the research and/or increases the quality of the solutions in a significant way.