用遗传算法改进战术计划

[1990] Proceedings of the 2nd International IEEE Conference on Tools for Artificial Intelligence Pub Date : 1990-11-06 DOI:10.1109/TAI.1990.130358

A. Schultz, J. Grefenstette

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引用次数: 64

摘要

研究了序列任务决策规则的学习问题，重点研究了从一个简单的飞行模拟器中学习战术计划的问题，其中飞机必须避开导弹。该学习方法基于竞争的概念，利用遗传算法搜索决策策略的空间。在这里提出的研究中，研究了使用可用的启发式领域知识来初始化种群以产生更好的计划。

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Improving tactical plans with genetic algorithms

The problem of learning decision rules for sequential tasks is addressed, focusing on the problem of learning tactical plans from a simple flight simulator where a plane must avoid a missile. The learning method relies on the notion of competition and uses genetic algorithms to search the space of decision policies. In the research presented here, the use of available heuristic domain knowledge to initialize the population to produce better plans is investigated.<>

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[1990] Proceedings of the 2nd International IEEE Conference on Tools for Artificial Intelligence

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