Lamarckian Learning in Multi-Agent Environments
Lamarckian Learning in Multi-Agent Environments
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发表时间：
1991
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通讯作者：
J. Grefenstette
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作者：
J. Grefenstette
翻译后摘要：遗传算法获得了很大的权力，来自人口遗传学领域的机制。然而，有可能，在某些情况下是可取的，以增加生物系统中没有的额外功能的标准机制。在本文中，我们研究使用拉马克学习算子的SAMUEL架构。在多智能体环境中的三个任务上说明了运营商的使用。（安）
Abstract : Genetic algorithms gain much of their power from mechanisms derived from the field of population genetics. However, it is possible, and in some cases desirable, to augment the standard mechanisms with additional features not available in biological systems. In this paper, we examine the use of Lamarckian learning operators in the SAMUEL architecture. The use of the operators is illustrated on three tasks in multi-agent environments. (AN)