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Influences of Artificial Speciation on Morphological Robot Evolution

机译:人工形态对形态机器人演化的影响

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One key challenge in Evolutionary Robotics (ER) is to evolve morphology and controllers of robots. Most experiments in the field converge rapidly to a single solution for the entire population. Early convergence results in a premature loss of diversity, which creates inconsistent results across multiple runs, sometimes converging to a local optimum. In Nature we can observe the opposite behavior: the more time passes, the more life becomes increasingly diverse. The increasing diversity is correlated to the formation of new species, which is catalyzed by reproductive isolation caused by physical or behavioral separation. Inspired by natural evolution, in this paper we apply artificial speciation based on morphological traits to an ER system. Individuals are forced to crossover only with individuals within the same species and a protection mechanism is applied to newly created species. In our experiments, we demonstrate that this speciation mechanism, inspired by NEAT, can evolve a population rich of many coexisting individuals, differing both in morphology and behavior.
机译:进化机器人(ER)中的一个关键挑战是进化机器人的形态和控制器。该领域的大多数实验将迅速收敛到整个人口的单一解决方案。早期收敛导致过早的多样性损失,这在多次运行中产生了不一致的结果,有时会融合到局部最优。在自然中,我们可以观察到相反的行为:时间越多,生活就越多样化。越来越多的多样性与新物种的形成相关,其通过物理或行为分离引起的生殖分离催化。在本文中受到自然演化的启发,我们将基于形态学的形态学应用于ER系统。个人仅被迫在同一物种内的个体交叉,并将保护机制应用于新创建的物种。在我们的实验中,我们证明这种由整洁的改进的这种形态机制可以发展丰富许多共存个人的人口,在形态和行为中不同。

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