PBIL algorithm is a probability learning based evolutionary algorithm.
PBIL算法是一种基于概率分析的进化算法。
This paper proposes an automatic negotiation algorithm based on co-evolutionary algorithm, and simulates the strategy learning mechanism in the finite horizon alternating offer negotiation protocol.
提出了基于协同进化遗传算法的自动谈判算法，模拟了有限期轮流出价谈判协议中的策略学习机制。
The algorithm is shown to be an evolutionary strategy capable of solving complex machine learning tasks, like multimode optimization.
这种革新算法能关于机器学习解复杂问题，实例结果表明，克隆选择算法对多峰值寻优问题有优良能力。
And through compare with non-Evolutionary Map building method, the Evolutionary Reinforcement learning algorithm can increase search map efficiency and expedite convergence speed of global map.
通过与非进化模式下的多机器人地图构建方法的比较，该算法可以提高地图搜索的效率，加快全局地图的收敛。
And through compare with non-Evolutionary Map building method, the Evolutionary Reinforcement learning algorithm can increase search map efficiency and expedite convergence speed of global map.
通过与非进化模式下的多机器人地图构建方法的比较，该算法可以提高地图搜索的效率，加快全局地图的收敛。
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