Explorations in evolutionary robotics
Explorations in evolutionary robotics
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DOI：
10.1177/105971239300200104
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发表时间：
1993-01-01
影响因子：
1.6
通讯作者：
Husbands, Phil
中科院分区：
文献类型：
--
作者：
Cliff, Dave;Harvey, Inman;Husbands, Phil
我们讨论了我们的工作的认知架构，或控制系统，位于自主代理的发展的方法论基础。我们的重点是移动的机器人的感觉运动控制系统的开发问题，但我们也讨论了我们的方法的生物系统的研究的适用性。我们认为，代理人需要表现出复杂的相互作用与他们的环境，复杂的感觉运动处理是必要的，和设计，通过手工，控制系统的这种处理能力可能会变得非常困难的复杂性增加。我们提出了一个自动设计过程，涉及人工进化，其中用于不断发展的认知架构的基本积木是噪声容忍的动态神经网络。这些网络可能是经常性的，并且应该在真实的时间内运作。进化应该是增量的，使用遗传算法的扩展和修改版本。实际的限制表明，最初的体系结构评估应该在很大程度上在模拟。为了支持我们的主张和建议，我们总结了一些初步的模拟实验中，视觉引导机器人的发展，在简单的环境中操作的结果。值得注意的是，我们的研究结果表明，强大的视觉引导控制系统的发展，不明确要求监控视觉输入的评价功能。我们概述了继续模拟所涉及的困难，并通过描述专门的visuorobotic设备，旨在消除对模拟传感器和执行器的需要。
We discuss the methodological foundations for our work on the development of cognitive architectures, or control systems, for situated autonomous agents. Our focus is the problems of developing sensorimotor control systems for mobile robots, but we also discuss the applicability of our approach to the study of biological systems. We argue that, for agents required to exhibit sophisticated interactions with their environments, complex sensorimotor processing is necessary, and the design, by hand, of control systems capable of such processing is likely to become prohibitively difficult as complexity increases. We propose an automatic design process involving artificial evolution, wherein the basic building blocks used for evolving cognitive architectures are noise-tolerant dynamical neural networks. These networks may be recurrent and should operate in real time. The evolution should be incremental, using an extended and modified version of a genetic algorithm. Practical constraints suggest that initial architecture evaluations should be done largely in simulation. To support our claims and proposals, we summarize results from some preliminary simulation experiments in which visually guided robots are evolved to operate in simple environments. Significantly, our results demonstrate that robust visually guided control systems evolve from evaluation functions that do not explicitly require monitoring visual input. We outline the difficulties involved in continuing with simulations and conclude by describing specialized visuorobotic equipment, designed to eliminate the need for simulated sensors and actuators.