This article describes the ExpertCop tutorial system, a simulator of crime in an urban region. In ExpertCop, the students (police officers) configure and allocate an available police force according to a selected geographic region and then interact with the simulation. The student interprets the results with the help of an intelligent tutor, the pedagogical agent, observing how crime behaves in the presence of the allocated preventive policing. The pedagogical agent implements interaction strategies between the student and the geosimulator, designed to make simulated phenomena better understood.

TEXTAL is a computer program that automatically interprets electron density maps to determine the atomic structures of proteins through X-ray crystallography. Electron density maps are traditionally interpreted by visually fitting atoms into density patterns. This manual process can be time-consuming and error prone, even for expert crystallographers. To automate the process, TEXTAL employs a variety of AI and pattern-recognition techniques that emulate the decision-making processes of domain experts.

A hybrid fuzzy knowledge-based system with crisp and fuzzy rules as well as numerical methods was developed for multiobjective optimization of power distribution system operation. The development process and knowledge-acquisition process for the fuzzy knowledge-based system are described in detail. After a heuristic preprocessor proposes a list of switch openings that would seem to reduce system losses, network radiality rules consider whether to open a particular switch and find a corresponding switch that can be closed to maintain radiality. Network performance rules find the degree of desirability of proposed switching combinations for enhancing multiple objectives.

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.

An end-to-end system was created at Genworth Financial to automate the underwriting of long-term care (LTC) and life insurance applications. Relying heavily on artificial intelligence techniques, the system has been in production since December 2002 and in 2004 completely automates the underwriting of 19 percent of the LTC applications. Finally, a natural language parser is used to improve the coverage of the underwriting system.

The Electrical Systems Division at the NASA Kennedy Space Center has developed and deployed an agent-based tool to monitor the space shuttle's ground processing telemetry stream. The agent provides autonomous monitoring of the telemetry stream and automatically alerts system engineers when predefined criteria have been met. Sandia National Labs' Java Expert System Shell is employed as the rule engine. This article discusses the rule-based telemetry agent used for space shuttle ground processing and explains the problem domain, development of the agent software, benefits of AI technology, and deployment and sustaining engineering of the product.

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.

In a field of research about general reasoning mechanisms, it is essential to have appropriate benchmarks. Ideally, the benchmarks should reflect possible applications of the developed technology. In AI Planning, researchers more and more tend to draw their testing examples from the benchmark collections used in the International Planning Competition (IPC). In the organization of (the deterministic part of) the fourth IPC, IPC-4, the authors therefore invested significant effort to create a useful set of benchmarks. They come from five different (potential) real-world applications of planning: airport ground traffic control, oil derivative transportation in pipeline networks, model-checking safety properties, power supply restoration, and UMTS call setup. Adapting and preparing such an application for use as a benchmark in the IPC involves, at the time, inevitable (often drastic) simplifications, as well as careful choice between, and engineering of, domain encodings. For the first time in the IPC, we used compilations to formulate complex domain features in simple languages such as STRIPS, rather than just dropping the more interesting problem constraints in the simpler language subsets. The article explains and discusses the five application domains and their adaptation to form the PDDL test suites used in IPC-4. We summarize known theoretical results on structural properties of the domains, regarding their computational complexity and provable properties of their topology under the h+ function (an idealized version of the relaxed plan heuristic). We present new (empirical) results illuminating properties such as the quality of the most wide-spread heuristic functions (planning graph, serial planning graph, and relaxed plan), the growth of propositional representations over instance size, and the number of actions available to achieve each fact; we discuss these data in conjunction with the best results achieved by the different kinds of planners participating in IPC-4.

Articles in this issue describe recent approaches for integrating algorithms and data structures from diverse subfields of AI. The new applications and significant improvements to existing applications this work has enabled demonstrates the ability of integrated systems and research to continue progress towards human-level artificial intelligence.