Evolution and development of neural controllers for locomotion, gradient-following, and obstacle-avoidance in artificial insects
Evolution and development of neural controllers for locomotion, gradient-following, and obstacle-avoidance in artificial insects
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DOI：
10.1109/72.712153
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发表时间：
1998-09-01
影响因子：
--
通讯作者：
Meyer, JA
中科院分区：
文献类型：
--
作者：
Kodjabachian, J;Meyer, JA
本文介绍了如何SGOCE范式已被用来发展能够产生控制模拟昆虫的行为的递归神经网络的发展计划。这种范式的特点是由一个编码方案，由一个进化算法，由语法约束，并依次描述的增量策略。此外，还使用了一个配备有六条腿和两个触角的昆虫模型，使其能够生成控制模块，使其能够连续地将梯度跟踪和避障能力添加到行走行为中。讨论了这种渐进方法的优点以及未来工作的方向。
This paper describes how the SGOCE paradigm has been used to evolve developmental programs capable of generating recurrent neural networks that control the behavior of simulated insects. This paradigm is characterized by an encoding scheme, by an evolutionary algorithm, by syntactic constraints, and by an incremental strategy that are described in turn. The additional use of an insect model equipped with six legs and two antennae made it possible to generate control modules that allowed it to successively add gradient-following and obstacle-avoidance capacities to walking behavior. The advantages of this evolutionary approach, together with directions for future work, are discussed.