Bullinaria John A
School of Computer Science, The University of Birmingham, Birmingham B15 2TT, UK.
Philos Trans A Math Phys Eng Sci. 2003 Oct 15;361(1811):2145-64. doi: 10.1098/rsta.2003.1249.
Attempts to formulate realistic models of the development of the human oculomotor control system have led to the conclusion that evolutionary factors play a crucial role. Moreover, even rather coarse simulations of the biological evolutionary processes result in adaptable control systems that are considerably more efficient than those designed by human researchers. In this paper I shall describe some of the aspects of these biological models that are likely to be useful for building robot control systems. In particular, I shall consider the evolution of appropriate innate starting points for learning/adaptation, patterns of learning rates that vary across different system components, learning rates that vary during the system's lifetime, and the relevance of individual differences across the evolved populations.
进化因素起着至关重要的作用。此外，即使是对生物进化过程相当粗略的模拟也会产生适应性控制系统，这些系统比人类研究人员设计的系统效率要高得多。在本文中，我将描述这些生物模型的一些方面，这些方面可能对构建机器人控制系统有用。特别是，我将考虑学习/适应的适当先天起点的进化、不同系统组件间变化的学习速率模式、系统生命周期内变化的学习速率，以及进化群体中个体差异的相关性。
