The 22nd International Florida Artificial Intelligence Research Society Conference (FLAIRS-22) was held 19th – 21st May 2009 at the Sundial Beach and Golf Resort on Sanibel Island, Florida, USA. It continued a long tradition of FLAIRS conferences, which attract researchers from around the world. The conference featured technical papers, special tracks, and invited speakers. The special tracks were coordinated by Philip McCarthy, from the University of Memphis.

This is an opinion piece about the relationship between the fields of human-computer interaction (HCI), and artificial intelligence (AI). There is an unjustified perception in HCI that AI is unreliable. There is an unjustified perception in AI that interfaces are merely cosmetic. This article argues that AI's goals of intelligent interfaces would benefit enormously by the user-centered design and testing principles of HCI.

The RADAR project developed a large multi-agent system with a mixed-initiative user interface designed to help office workers cope with email overload. Most RADAR agents observe experts performing tasks and then assist other users who are performing similar tasks. The interaction design for RADAR focused on developing user interfaces that allowed the intelligent functionality to improve the user's workflow without frustrating the user when the system's suggestions were either unhelpful or simply incorrect. A large evaluation of RADAR demonstrated that novice users confronted with an email overload test performed significantly better, achieving a 37% better overall score when assisted by RADAR.

When creating algorithms or systems that are supposed to be used by people, we should be able to adopt a "binocular" view of users' interaction with intelligent systems: a view that regards the design of interaction and the design of intelligent algorithms as interrelated parts of a single design problem. This special issue offers a coherent set of articles on two levels of generality that illustrate the binocular view and help readers to adopt it.

This case study article describes the iterative design process of an adaptive, mixed-initiative calendaring tool with embedded artificial intelligence. We establish the specific types of assistance in which the target user population expressed interest, and we highlight our findings regarding the scheduling practices and the reminding preferences of these users. These findings motivated the redesign and enhancement of our intelligent system. Lessons learned from the study--namely, highlighting the merits of usability toward widespread adoption and retention, and that simple problems that perhaps do not necessitate complex AI-based solutions should not go unattended merely due to their inherent simplicity--conclude the article, along with a discussion of the importance of the iterative design process for any user adaptive system.

The titles of the nine symposia were Agents that Learn from Human Teachers, Benchmarking of Qualitative Spatial and Temporal Reasoning Systems, Experimental Design for Real-World Systems, Human Behavior Modeling, Intelligent Event Processing, Intelligent Narrative Technologies II, Learning by Reading and Learning to Read, Social Semantic Web: Where Web 2.0 Meets Web 3.0, and Technosocial Predictive Analytics. The aim of the Benchmarking of Qualitative Spatial and Temporal Reasoning Systems symposium was to initiate the development of a problem repository in the field of qualitative spatial and temporal reasoning and identify a graded set of challenges for future midterm and long-term research. The Intelligent Event Processing symposium discussed the need for more AI-based approaches in event processing and defined a kind of research agenda for the field, coined as intelligent complex event processing (iCEP). The Intelligent Narrative Technologies II AAAI symposium discussed innovations, progress, and novel techniques in the research domain.

NASA and the United States Geological Survey (USGS) are collaborating to produce a global map of the Earth using Landsat 5 Thematic Mapper (TM) and Landsat 7 Enhanced Thematic Mapper Plus (ETM) remote sensor data from the period of 2004 through 2007. Constraints and preferences on map quality make it desirable to develop an automated solution to the map generation problem. This paper formulates a Global Map Generator problem as a Constraint Optimization Problem (GMG-COP) and describes an approach to solving it using local search. The paper also describes the integration of a GMG solver into a graphical user interface for visualizing and comparing solutions, thus allowing for solutions to be generated with human participation and guidance.

The goal of the Innovative Applications of Artificial Intelligence (IAAI) conference is to highlight new, innovative, systems and application areas of AI technology and to point out the often-overlooked difficulties involved in deploying complex technology to end users. Those of us who have ventured out of the realm of pure research and tried to build applications to be used by our fellow humans realize that it takes a lot more than just brilliant algorithms to make an application survive in the real world. Each application that succeeds is worth celebrating and the teams behind them are due wholehearted congratulations. It is in this spirit that we bring you this special issue covering select applications from the IAAI conference held last year in Chicago.

CSIEC (Computer Simulation in Educational Communication), is not only an intelligent web-based human-computer dialogue system with natural language for English instruction, but also a learning assessment system for learners and teachers. Its multiple functions--including grammar-based gap filling exercises, scenario show, free chatting and chatting on a given topic--can satisfy the various requirements for students with different backgrounds and learning abilities. We will summarize the free Internet usage within a six month period and its integration into English classes in universities and middle schools. The evaluation findings about the class integration show that the chatting function has been improved and frequently utilized by the users, and the application of the CSIEC system on English instruction can motivate the learners to practice English and enhance their learning process.

The Tactical Language and Culture Training System (TLCTS) helps people quickly acquire communicative skills in foreign languages and 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 dialog, 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.