We have developed an autonomous robot system that takes well-composed photographs of people at social events, such as weddings and conference receptions. In this article, we outline the overall architecture of the system and describe how the various components interrelate. We also describe our experiences deploying the robot photographer at a number of real-world events.

The concept of precisiated natural language (PNL) was briefly introduced in that article, and PNL was employed as a basis for computation with perceptions. In what follows, the conceptual structure of PNL is described in greater detail, and PNL's role in knowledge representation, deduction, and concept definition is outlined and illustrated by examples. Thus, we have partial understanding, partial truth, partial possibility, partial certainty, partial similarity, and partial relevance, to cite a few examples. As it matures, PNL is likely to find a variety of applications, especially in the realms of world knowledge representation, concept definition, deduction, decision, search, and question answering.

Sketch maps are an important spatial representation used in many geospatial-reasoning tasks. This article describes techniques we have developed that enable software to perform humanlike reasoning about sketch maps. We illustrate the utility of these techniques in the context of nuSketch Battlespace, a research system that has been successfully used in a variety of experiments. After an overview of the nuSketch approach and nuSketch Battlespace, we outline the representations of glyphs and sketches and the nuSketch spatial reasoning architecture.

We are pleased to publish this special selection of papers from the 2003 Innovative Applications of Artificial Intelligence Conference (IAAI-03). IAAI seeks out applications of artificial intelligence that either demonstrate new technology or use previously known technology in innovative ways. IAAI particularly seeks out examples of deployments of AI technology that tackle the problems of demonstrating value and planning for long-term deployment. Two of the articles are deployed applications that have already demonstrated practical value.

In this article, we describe a deployed educational technology application: the Criterion Online Essay Evaluation Service, a web-based system that provides automated scoring and evaluation of student essays. Criterion has two complementary applications: (1) CritiqueWriting Analysis Tools, a suite of programs that detect errors in grammar, usage, and mechanics, that identify discourse elements in the essay, and that recognize potentially undesirable elements of style, and (2) e-rater version 2.0, an automated essay scoring system. Critique and e-rater provide students with feedback that is specific to their writing in order to help them improve their writing skills and is intended to be used under the instruction of a classroom teacher. All of these capabilities outperform baseline algorithms, and some of the tools agree with human judges in their evaluations as often as two judges agree with each other.

AI agents combining natural language interaction, task planning, and business ontologies can help companies provide better-quality and more costeffective customer service. Our customer-service agents use natural language to interact with customers, enabling customers to state their intentions directly instead of searching for the places on the Web site that may address their concern. Our agents converse with customers, guaranteeing that needed information is acquired from customers and that relevant information is provided to them in order for both parties to make the right decision. The net effect is a more frictionless interaction process that improves the customer experience and makes businesses more competitive on the service front.

The Twelfth Annual Association for the Advancement of Artificial Intelligence (AAAI) Robot Competition and Exhibition was held in Acapulco, Mexico, in conjunction with the Eighteenth International Joint Conference on Artificial Intelligence. The events included the Robot Host and Urban Search and Rescue competitions, the AAAI Robot Challenge, and the Robot Exhibition. In the Urban Search and Rescue competition, teams attempted to find victims in a simulated disaster area using teleoperated, semiautonomous, and autonomous robots. The AAAI Robot Challenge is a noncompetitive event where the robots attempt to attend the conference by locating the registration booth, registering for the conference, and then giving a talk to an audience.

An adequate natural language description of developments in a real-world scene can be taken as proof of "understanding what is going on." An algorithmic system that generates natural language descriptions from video recordings of road traffic scenes can be said to "understand" its input to the extent that algorithmically generated text is acceptable to the humans judging it. A fuzzy metrictemporal Horn logic (FMTHL) provides a formalism for representing both schematic and instantiated conceptual knowledge about the depicted scene and its temporal development. The resulting conceptual representation mediates in a systematic manner between the spatiotemporal geometric descriptions extracted from video input and a module that generates natural language text.

To build a machine that has "common sense" was once a principal goal in the field of artificial intelligence. But most researchers in recent years have retreated from that ambitious aim. We are convinced, however, that no one such method will ever turn out to be "best," and that instead, the powerful AI systems of the future will use a diverse array of resources that, together, will deal with a great range of problems. To build a machine that's resourceful enough to have humanlike common sense, we must develop ways to combine the advantages of multiple methods to represent knowledge, multiple ways to make inferences, and multiple ways to learn.