The Stanford Heuristic Programming Project: Goals and Activities

Publications that have influenced the growth of artificial intelligence are often difficult to obtain. We first collected titles of several thousand publications from many well-known sources and then selected about 1850 titles considered to be especially influential. We have identified, and in a few cases created, online versions of about half of these "classics in AI." Searchable text of the documents enables additional analysis of trends and influences.

Publications that have influenced the growth of artificial intelligence are often difficult to obtain.  We first collected titles of several thousand publications from many well-known sources and then selected about 1850 titles considered to be especially influential.  We have identified, and in a few cases created, online versions of about half of these “classics in AI.”  Searchable text of the documents enables additional analysis of trends and influences.  Integration into the rest of the AITopics information portal contextualizes the classic publications.

NewsFinder automates the steps involved in finding, selecting, categorizing, and publishing news stories that meet relevance criteria for the Artificial Intelligence community. The software combines a broad search of online news sources with topic-specific trained models and heuristics. Since August 2010, the program has been used to operate the AI in the News service that is part of the AAAI AITopics website.

The AAAI video archive is a central source of information about videotapes and films with information about AI that are stored digitally on other sites or physically in institutional archives. For each video, the archive includes a brief description of the contents and personae, one or more representative short clips for classroom or individual use, and the location of the archival copy (for example, at a university library).

However, the simple equation "knowledge is power" leaves three major questions unanswered. First, what do we mean by "knowledge"; second, what do we mean by "power"; and third, what do we mean by "is"? In this article, I will examine the first of these questions. The discipline and detail required to write programs that use knowledge have given us some valuable lessons for implementing the knowledge principle, one of which is to make our programs as flexible as we can.

What Do We Know about Knowledge? In this article, I will examine the first of these questions. AI has been slow to embrace this principle. Programs demonstrating research ideas in AI are often too large and not well enough documented to allow replication or sharing. What I would like to in diverse conditions. I wish to clarify the knowledge example, it was pretty clearly articulated in Biblical principle and try to increase our understanding times: "A man of knowledge increaseth of what programmers and program strength" (Proverbs 24: 5). Greek philosophers based their lives on acquiring The "knowledge is power" principle is most and transferring knowledge. In the course closely associated with Francis Bacon, from his of teaching, they sought to understand the 1597 tract on heresies: "Nam et ipsa scientia nature of knowledge and how we can establish potestas est." ("In and of itself, knowledge is knowledge of the natural world. B," along with quantification, "All A's are B's," Euclid's geometry firmly established the concept In the intervening several centuries before Plato, Socrates's pupil and Aristotle's mentor, was the first to pose the question in writing of the Middle Ages and the rise of modern science what we mean when we say that a person in the West, He was distinguishing empirical knowledge, church to make new knowledge fit with established lacking complete certainty, from the certain dogma.

In this brief history, the beginnings of artificial intelligence are traced to philosophy, fiction, and imagination. Early inventions in electronics, engineering, and many other disciplines have influenced AI. Some early milestones include work in problems solving which included basic work in learning, knowledge representation, and inference as well as demonstration programs in language understanding, translation, theorem proving, associative memory, and knowledge-based systems. The article ends with a brief examination of influential organizations and current issues facing the field.

This article provides a historical background on the origins of AAAI, recounting some of the issues discussed and requirements to be fulfilled by the new society. It provides a personal reminiscence of some of the persons who founded the association, including Raj Reddy, Donald Walker, and Woody Bledsoe, and also recounts some of my experiences as secretarytreasurer and later president of AAAI. In 1979 he was the general chair for IJCAI-79, and I was the program chair, so we were already working closely together and thinking about organization. We were not alone in being frustrated by the phoenix-like nature of IJCAI--springing to life before every biannual conference, then dying, with little continuity. Also, it was obvious that volunteers from academe and industry had numerous distractions and other obligations besides IJCAI, so important deadlines could easily be missed.

In this brief history, the beginnings of artificial intelligence are traced to philosophy, fiction, and imagination. Early inventions in electronics, engineering, and many other disciplines have influenced AI. Some early milestones include work in problems solving which included basic work in learning, knowledge representation, and inference as well as demonstration programs in language understanding, translation, theorem proving, associative memory, and knowledge-based systems. The article ends with a brief examination of influential organizations and current issues facing the field.