Robotics is a remarkable domain that may be successfully employed in the classroom both to motivate students to tackle hard AI topics and to provide students experience applying AI representations and algorithms to real-world problems. This article uses two example robotics problems to illustrate these themes. We show how the robot obstacle-detection problem can motivate learning neural networks and Bayesian networks. We also show how the robot-localization problem can motivate learning how to build complete solutions based on particle filtering. Since these lessons can be replicated on many low-cost robot platforms they are accessible to a broad population of AI students. We hope that by outlining our educational exercises and providing pointers to additional resources we can help reduce the effort expended by other educators. We believe that expanding handson active learning to additional AI classrooms provides value both to the students and to the future of the field itself. One particularly compelling domain is robotics. Robotics combines the fantasy of science fiction with practical real-world applications and engages both the imaginative and sensible sides of students. In addition to providing inspiration, exploring artificial intelligence representations and algorithms using robotics helps students to learn complete solutions. A complete solution is one in which a student considers all the details of implementing AI algorithms in a realworld environment. These details range from system design, to algorithm selection and implementation, to behavior analysis and experimentation, to making the solution robust in the face of uncertainty. In our classes we find that robotics problems encourage students to investigate how AI algorithms interact with each other, with non-AI solutions, and with a real-world environment. Students investigate how to convert sensor data into internal data structures, how to weigh the costs and benefits of physical exploration, whether or not to use offline simulation and tools, and how to deal with the severe resource limitations and time constraints of embedded computation. Despite the added costs of building complete solutions, experience with real-world environments helps ground lessons and stimulates thinking about new challenges and solutions.

Robotics projects coupled with agent-oriented trends in artificial intelligence education have the potential to make introductory AI courses at liberal arts schools the gateway for a large new generation of AI practitioners. However, this vision's achievement requires programming libraries and low-cost platforms that are readily accessible to undergraduates and easily maintainable by instructors at sites with few dedicated resources. This article presents and evaluates one contribution toward implementing this vision: the RCXLisp library. The library was designed to support programming of the Lego Mindstorms platform in AI courses with the goal of using introductory robotics to motivate undergraduates' understanding of AI concepts within the agent-design paradigm. The library's evaluation reflects four years of student feedback on its use in a liberal-arts AI course whose audience covers a wide variety of majors. To help establish a context for judging RCXLisp's effectiveness this article also provides a sketch of the Mindstormsbased laboratory in which the library is used. Today AI should be poised to capture students' interest and imaginations in the same way that movie showed one application in physics and astronomy capturing them in the 1950s and 1960s. Look at what today's undergraduates are seeing and hearing about AI in popular culture. Besides the popularity of the AIinspired fiction in the movies I, Robot and A.I., consider the highly publicized success of the Mars rovers Spirit and Opportunity, the ESPN coverage of the DARPA autonomous vehicle Grand Challenge, the lust among gamers after cleverer computer opponents, and the prevalence of word processor speech-recognition systems. Students are not just hearing about AI applications--they are experiencing them more directly than did the students in October Sky gazing up at Sputnik's starlike dot. Today's college and high school students can evaluate AI applications firsthand (for example, in games, robotic vacuum cleaners, and intelligent search engines). More importantly for AI, the immediacy of their experience often makes them feel they could replicate or even improve the applications' capabilities--if only they understood the AI theory behind the application. And this situation definitely is enticing students into trying out introductory AI courses at liberal arts colleges. The difficulty for instructors at such schools is retaining these students' interest in the field after their first exposure to formal AI. In many smaller schools' computer science departments there is at most one faculty member with AI training, usually with few dedicated resources.

The Nineteenth International FLAIRS Conference (FLAIRS-19) was held 11-13 May 2006 at the Crowne Plaza Melbourne Oceanfront Hotel in Melbourne Beach, FL. The general cochairs were Philip Chan and Debasis Mitra, from the Florida Institute of Technology. The program cochairs were Geoff Sutcliffe, from the University of Miami, and Randy Goebel, from the University of Alberta. The special tracks chair was Barry O'Sullivan, from University College Cork. The conference was attended by almost 200 AI researchers from around the world.

Another popular event at the DC was the student-mentor dinner, held this year at Elephant Walk, which provided an opportunity for students and researchers to interact in an informal setting. We report on the eleventh annual SIGART/AAAI Doctoral Consortium, held in conjunction with the National Conference on Artificial Intelligence (AAAI-06). We discuss highlights and innovations of this year's consortium and include pointers to the consortium website. At the DC, Ph.D. students in artificial intelligence presented their proposed research and received feedback from a panel of researchers and other students. The primary goal of the DC is to give students feedback on their proposed dissertation research at a critical time, by independent, knowledgeable reviewers external to their institutions.

The Fifteenth Annual AAAI Robot Competition and Exhibition was held at the National Conference on Artificial Intelligence in Boston, Massachusetts, in July 2006. This article describes the events that were held at the conference, including the Scavenger Hunt, Human Robot Interaction, and Robot Exhibition. The robot competition and exhibition has a long tradition of demonstrating innovative research in robotics (Rybski et al. 2006, Smart et al. 2005, Balch and Yanco 2005). From new approaches to canonical robotics problems to groundbreaking research in emerging areas, the robot program provides a forum for a diverse range of projects in mobile robotics. Recent years have witnessed a rise in the accessibility of mobile robot platforms with reasonably capable platforms being available for relatively low cost (Dodds and Tribblehorn 2006, Dodds et al. 2004) and not requiring a substantial effort to build hardware (Veloso et al. 2006) or software (Blank et al. 2003, Touretzky and Tira-Thompson 2005) architectures.

Since more and more people look to the web for information--sometimes exclusively--providing information online is an effective way to reach the public and fulfill this obligation. The site has grown to include a variety of textual materials including overviews, news stories, technical articles, and some audio and video materials about AI. While search engines such as Google and Yahoo will find everything online that mentions a topic of interest, a mediated site such as AI Topics offers well-written, accurate materials that provide good starting places for learning about the topic and paves the way for further exploration. The AI Topics site is heavily used by a diverse group of visitors from around the world, and our statistics show that usage has increased steadily over the years. Spikes in the usage charts around the ends of academic terms suggest that students are using the site to find material for term papers and projects.

The Fourth IET International Conference on Intelligent Environments was held July 21-22 at the University of Washington campus in Seattle, Washington. The general chairs were Diane Cook of Washington State University and Sumi Helal of the University of Florida. Hani Hagras and Vic Callaghan of the University of Essex served as program chairs. This article presents a report of the conference. The conference aims at contributing to the realization of the ambient intelligence vision, where physical space becomes augmented with computation, communication, and digital content, thus transcending the limits of direct human perception.

In 2008, the AAAI Robotics organizers eschewed the previous format of a Robot Competition, choosing instead to focus on groundbreaking work representing two areas of robotics: creativity and mobility and manipulation (detailed in a separate article). Both workshops were held on July 14, and the Robotics Exhibition included participants from both categories. The Robotics and Creativity Workshop was made possible through the support of the National Science Foundation's CreativeIT program and Microsoft Research. Developments in mechanical control and complex motion planning have enabled robots to become almost commonplace in situations requiring precise but menial, tedious, and repetitive tasks. Recent robotics research has targeted the mechanical and computational challenges inherent in performing a much broader range of tasks autonomously.

The titles of the seven symposia were (1) Adaptive Agents in Cultural Contexts, (2) AI in Eldercare: New Solutions to Old Problems, (3) Automated Scientific Discovery, (4) Biologically Inspired Cognitive Architectures, (5) Education Informatics: Steps toward the International Internet Classroom, (6) Multimedia Information Extraction, and (7) Naturally Inspired AI. The goal of the Adaptive Agents in Cultural Contexts symposium was to investigate agents and environments for behavior in social and cultural contexts and for realistic adaptation of such agents to changing situations. These fields are vast, variegated, informed by disparate theoretical and technical disciplines, and interrelated. This symposium was intended to examine the intersection of findings from the field, theory, and applications in such areas as autonomous agent models and simulations for research, international commercial enterprise, nongovernmental organizations, and military, as well as commercial, games. The symposium began with an invited talk given by psychologist Helen Klein of Wright State University, who addressed the dimensions of culturally specific cognition and surveyed behavioral phenomena across cultures.

More than 40,000 learners worldwide have used TLCTS courses. TLCTS utilizes artificial intelligence technologies during the authoring process and at run time to process learner speech, engage in dialogue, and evaluate and assess learner performance. This paper describes the architecture of TLCTS and the artificial intelligence technologies that it employs and presents results from multiple evaluation studies that demonstrate the benefits of learning foreign language and culture using this approach. It includes interactive lessons that focus on particular communicative skills and interactive games that apply those skills. Heavy emphasis is placed on spoken communication: learners must learn to speak the foreign language to complete the lessons and play the games.