Imagine an Internet-scale knowledge system where people and intelligent agents can collaborate on solving complex problems in business, engineering, science, medicine, and other endeavors. Its resources include semantically tagged websites, wikis, and blogs, as well as social networks, vertical search engines, and a vast array of web services from business processes to AI planners and domain models. Research prototypes of decentralized knowledge systems have been demonstrated for years, but now, thanks to the web and Moore's law, they appear ready for prime time. This article introduces the architectural concepts for incrementally growing an Internet-scale knowledge system and illustrates them with scenarios drawn from e-commerce, e-science, and e-life.

The Association for the Advancement of Artificial Intelligence, in cooperation with Stanford University's Computer Science Department, was pleased to present its 2006 Spring Symposium Series held March 27-29, 2006, at Stanford University, California.

The Fourteenth Annual AAAI Mobile Robot Competition and Exhibition was held at the National Conference on Artificial Intelligence in Pittsburgh, Pennsylvania, in July 2005. This year marked a change in the venue format from a conference hall to a hotel, which changed how the robot event was run. As a result, the robots were much more visible to the attendees of the AAAI conference than in previous years. This article describes the events that were held at the conference, including the Scavenger Hunt, Open Interaction, Robot Challenge, and Robot Exhibition.

The first international conference on human-robot interaction (HRI2006) was held in Salt Lake City, Utah, on March 2-4, 2006. The conference included posters and paper presentations, with topics including metrics and testbeds, natural and affective interaction, cognitive robotics, interfaces, robot teams, usability, and learning. Approximately 150 researchers and practitioners attended the conference, and many more contributed to the conference as authors or reviewers. HRI2007 will be held in Washington, D.C., in March 2007.

Sabater described current research in the area, presenting some of the current research lines and the shortcomings of present approaches. He also outlined some of the topics in which information-fusion and aggregation operators can play a role. The conference papers were published in Springer Verlag's Lecture Notes in Artificial Intelligence series (volume 3885). Further information on the series is available at mdai.cat. The next MDAI conference will be held August 16-18, 2007, in Kitakyushu, Japan.

CMRoboBits is a course offered at Carnegie Mellon University that introduces students to all the concepts needed to create a complete intelligent robot. This course shows how an AIBO and its software resources make it possible for students to investigate and work with an unusually broad variety of AI topics within a single semester. While material presented in this article describes using AIBOs as the primary platform, the concepts presented in the course are not unique to the AIBO and can be applied on different kinds of robotic hardware.

This article introduces Pyro, an open-source Python robotics toolkit for exploring topics in AI and robotics.

We examine the marriage of recent probabilistic generative models for social networks with classical frameworks from mathematical economics. Weare particularly interested in how the statistical structure of such networks influences global economic quantities such as price variation. Ourfindings are a mixture of formal analysis, simulation, and experiments on an international trade data set from the United Nations.

We examine the marriage of recent probabilistic generative models for social networks with classical frameworks from mathematical economics. We are particularly interested in how the statistical structure of such networks influences global economic quantities such as price variation. Our findings are a mixture of formal analysis, simulation, and experiments on an international trade data set from the United Nations.

Two neural networks that are trained on their mutual output synchronize to an identical time dependant weight vector. This novel phenomenon can be used for creation of a secure cryptographic secret-key using a public channel. Several models for this cryptographic system have been suggested, and have been tested for their security under different sophisticated attackstrategies. The most promising models are networks that involve chaos synchronization. The synchronization process of mutual learning is described analytically using statistical physics methods.