Synthetic ethology and the evolution of cooperative communication
Adaptive Behavior
Genetic programming and AI planning systems
AAAI'94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 2)
Increasing Population Diversity Through Cultural Learning
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
An overview of evolutionary algorithms for parameter optimization
Evolutionary Computation
Diversity in genetic programming: an analysis of measures and correlation with fitness
IEEE Transactions on Evolutionary Computation
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Cultural learning allows individuals to acquire knowledge from others through non-genetic means. The effect of cultural learning on the evolution of artificial organisms has been the focus of much research. This paper examines the effects of cultural learning on the fitness and diversity of a population and, in addition, the effect of self-adaptive cultural learning parameters on the evolutionary process. The NK fitness landscape model is employed as the problem task and experiments employing populations endowed with both evolutionary and cultural learning are compared to those employing evolutionary learning alone. Our experiments measure the fitness and diversity of both populations and also track the values of two self-adaptive cultural parameters. Results show that the addition of cultural learning has a beneficial effect on the population in terms of fitness and diversity maintenance. Furthermore, analysis of the self-adaptive parameter values shows the relative quality of the cultural process throughout the experiment and highlights the benefits of self-adaptation over fixed parameter values.