PYI: Computational Systems Based Upon Aspects of the Immune System

这是五年PYI持续奖励的第一年基本资金。在线智能系统（自然的或人工的）必须响应实时约束，与环境同步，并能够不断地调整其行为以适应动态环境。此外，如果我们要有效地利用大规模和高度复杂的计算环境，自适应机制必须在许多层面上发挥核心作用。这些陈述为本研究提供了依据。自调整数据结构是如何在传统计算框架中利用自适应原则的一个简单示例。一种更激进的方法是利用非线性动力学的见解来设计系统，其中许多低级相互作用的自适应单元产生一个全局动态，计算出一些有用的功能。后一种方法在本文中被称为“紧急计算”。分类系统和其他计算生态提供了这样的系统是可行的证据。免疫系统提供了一个在局部水平运行的适应和在全球水平出现的有用行为（例如识别抗原）的优秀模型，并将被用作本工作的分析领域。

This is the first year base amount funding of a five year PYI continuing award. On-line intelligent systems (natural or artificial) must respond to real-time constraints, synchronize themselves with their environments, and be capable of adapting their behavior continuously to dynamic environments. Furthermore, adaptive mechanisms must play a central role at manylevels if we are to utilize large-scale and highly complex computing environments effectively. These statements provide thebasis for this research. Self-adjusting data structures are a simple example of how adaptive principles can be exploited within a traditional computing framework. A more radical approach uses insights from nonlinear dynamics to design systems in which many low-level interacting adaptive units produce a global dynamics that computers some useful function. This latter approach is refer to in this effort as "emergent computation." Classifier systems and other computational ecologies provide evidence that such systems are feasible. The immune system provides an excellent model of adaption operating at the local level and of useful behavior (e.g. recognizing antigens) emerging at the global level and will be used as the domain of analysis for this work.