On agent-based software engineering
Artificial Intelligence
Introduction to Multiagent Systems
Introduction to Multiagent Systems
Comparing Synchronous and Asynchronous Cellular Genetic Algorithms
PPSN VII Proceedings of the 7th International Conference on Parallel Problem Solving from Nature
Proceedings of the 10th annual conference companion on Genetic and evolutionary computation
Asynchronous collaborative search using adaptive co-evolving subpopulations
Proceedings of the 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference: Late Breaking Papers
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A Geometric Collaborative Evolutionary (GCE) model is presented and studied. An asynchronous search process is facilitated through a gradual propagation of the fittest individuals' genetic material into the population. Recombination is guided by the geometrical structure of the population. The GCE model specifies three strategies for recombination corresponding to three subpopulations (societies of agents). Each individual in the population acts as an autonomous agent with the goal of optimizing its fitness being able to communicate and select a mate for recombination. Complex dynamics in the proposed system are investigated against the probability of dominance between agent societies. A significant emergent pattern and corresponding transition interval are emphasized in several experiments. Percolation-like behavior is also detected, suggesting the complete dominance of one agent society over the entire population under certain conditions. Furthermore, numerical results indicate a good performance of the proposed evolutionary asynchronous search model.