Workshop on Approaches to Artificial Intelligence, Santa Fe,New Mexico, November 1992

人工智能(AI)领域的目标是开发能够像人类一样、甚至可能比人类更好地在复杂环境中感知、推理、交流和行动的机器。尽管该领域已经生产出了一些实用的机器，具有这些能力的雏形，但人们普遍承认，最终目标仍然遥远。既然如此，在为实现最终目标奠定核心基础的意义上，以及在产生实际有用的短期结果的意义上，关于人工智能的最佳方法是什么，存在着许多讨论和争论。因此，在过去35年左右的时间里，出现了许多不同的范式。每一种都有其热心的倡导者，其中一些已经产生了足够多的有趣的结果，以至于不会被立即解雇。或许这些方法的结合将是必要的。无论如何，这些方法的倡导者往往认为他们的方法是值得特别支持的“突破性”方法。为了使研究人员和其他人熟悉这些范例及其主要成果，圣达菲研究所组织了一次讲习班，将邀请积极从事不同方法工作的倡导者参加。这样的工作坊可以让领导员工了解彼此的观点以及他们之间的关系。具体地说，研讨会并不是围绕经典的人工智能的主要子学科组织的，即机器视觉、自然语言处理、知识表示、规划、专家系统等。取而代之的是，对于应该如何攻击人工智能的整个或主要部分，提出了不同的观点。

The field of artificial intelligence (AI) has as its goal the development of machines that can perceive, reason, communicate, and act in complex environments much like humans can, or possibly even better than humans can. Even though the field has produced some practically useful machines with rudiments of these abilities, it is generally conceded that the ultimate goal is still distant. That being so, there is much discussion and argument about what are the best approaches for AI in the sense of laying the core foundations for achieving ultimate goals as well as best in the sense of producing practically useful shorter-term results. Thus, a number of different paradigms have emerged over the past thirty-five years or so. Each has its ardent advocates, and some have produced sufficiently many interesting results so as not to be dismissable out of hand. Perhaps combinations of these approaches will be required. In any case, the advocates of these approaches often feel that theirs is the "breakthrough" methodology that deserves special support. In order to acquaint researchers and others with these paradigms and their principal results, the Santa Fe Institute organizes a workshop to which advocates actively working in the different approaches will be invited. Such a workshop allows leading workers to understand each others' points of view and the relationships among them. Specifically the workshop is not organized around what classically have been the main sub-disciplines of AI, namely machine vision, natural language processing, knowledge representation, planning, expert systems, and so on. Instead, different perspectives are presented on how the whole, or major parts, of AI ought to be attacked.