This is a wonderful opportunity, yet a position is very hard to match in any other. The first AAAI conference was held at Stanford University; it was very much a research conference, a scientific event that generated a lot of excitement. The conference was small and intimate, with few parallel sessions. There were excellent opportunities for us to talk to one another. AAAI-80 gave real substance to the organization, clearly getting AAAI off on the right foot, and it gave new identity and cohesiveness to the field. This year--2006--has also been a big year, celebrating the 50th anniversary of the original meeting at Dartmouth College, where the name "artificial intelligence" first came into common use. Numerous events around the world, including a celebratory symposium at Dartmouth and an AAAI Fellows Symposium associated with AAAI-05, have marked this important milestone in the history of the field. Progress since our first AAAI conference has The First AAAI Conference was Held at Stanford University. While each year's results may have seemed incremental, when we look back over the entire period we see some truly amazing plate the big picture and, perhaps more importantly things. In job at DARPA), to identify gaps in our national hindsight this may no longer look so exciting computing research agenda. It also occurred to (purists will say that it was not an "AI" system me that that perspective was a very special that beat Garry Kasparov but rather a highly asset to use in drafting this presidential engineered special-purpose machine largely address. Looking forward from back then, no want to raise a broad issue and consider matter how Deep Blue actually worked, playing some larger questions regarding the nature of chess well was clearly an AI problem--in fact, a the field itself and the role that AAAI as an classical one--and our success was historic.

The celebration then moved to web and integrated intelligence, as on Artificial Intelligence and Boston where a huge turnout of AAAI well as the nectar and senior member the Nineteenth Innovative Applications fellows--from founding luminaries to papers, is a significant factor in this of Artificial Intelligence Conference 2006 fellow inductees--reported a trend." Senior member papers are a commemorated fifty years of great weekend meeting prior to the way to collect reflections about areas artificial intelligence research in AAAI conference full of discussions of work by leaders in the field.

The Workshop program of the Twenty-First Conference on Artificial Intelligence was held July 16-17, 2006 in Boston, Massachusetts. The program was chaired by Joyce Chai and Keith Decker. The titles of the 17 workshops were AIDriven Technologies for Service-Oriented Computing; Auction Mechanisms for Robot Coordination; Cognitive Modeling and Agent-Based Social Simulations, Cognitive Robotics; Computational Aesthetics: Artificial Intelligence Approaches to Beauty and Happiness; Educational Data Mining; Evaluation Methods for Machine Learning; Event Extraction and Synthesis; Heuristic Search, Memory- Based Heuristics, and Their Applications; Human Implications of Human-Robot Interaction; Intelligent Techniques in Web Personalization; Learning for Search; Modeling and Retrieval of Context; Modeling Others from Observations; and Statistical and Empirical Approaches for Spoken Dialogue Systems.

The special tracks chair was Barry O'Sullivan, FLAIRS Conference (FLAIRS-19) was Reversals via Representational Refinements"; held 11-13 May 2006 at the Crowne Bob Morris of the NASA Ames The 20th International FLAIRS Conference (FLAIRS-20) will be held May 7 - 9, 2007 at the Casa Marina Resort, which is directly on the beach in Key West, Florida, USA. FLAIRS-20 will feature technical papers, special tracks, and invited speakers on artificial intelligence. The conference is hosted by the Florida Artificial Intelligence Research General Chair Society, in cooperation with AAAI. Geoff Sutcliffe In addition to the general conference, FLAIRS offers numerous special conference tracks. Special tracks provide researchers in focused areas the opportunity to meet and present University of Miami their work.

We Papers submitted to the II track should For a complete list of deadlines, program are delighted to announce this permanent highlight synergistic effects of integrating information, and to check for change as we expand the venue components from distinct areas further updates, please visit the AAAIfor the conference throughout the of AI to achieve intelligent behavior.

In this paper we propose a data intensive approach for inferring sentence-internal temporal relations. Temporal inference is relevant for practical NLP applications which either extract or synthesize temporal information (e.g., summarisation, question answering). Our method bypasses the need for manual coding by exploiting the presence of markers like ``after", which overtly signal a temporal relation. We first show that models trained on main and subordinate clauses connected with a temporal marker achieve good performance on a pseudo-disambiguation task simulating temporal inference (during testing the temporal marker is treated as unseen and the models must select the right marker from a set of possible candidates). Secondly, we assess whether the proposed approach holds promise for the semi-automatic creation of temporal annotations. Specifically, we use a model trained on noisy and approximate data (i.e., main and subordinate clauses) to predict intra-sentential relations present in TimeBank, a corpus annotated rich temporal information. Our experiments compare and contrast several probabilistic models differing in their feature space, linguistic assumptions and data requirements. We evaluate performance against gold standard corpora and also against human subjects.

Rob Miller (Massachusetts Institute of Technology) will be held July 22-26, 2007 in Vancouver, Holger Hoos (University of British Columbia) British Columbia, Canada.

Two overarching goals were promoted for the 2005 Mobile Robot Competition. The first was to give the competitions an exhibitionstyle format to make them as accessible to different areas of research as possible. This was change would place the competitions and exhibitions demonstrated at the Fourteenth Annual AAAI directly in line with the conference, Mobile Robot Competition and Exhibition, an teams would need to handle the challenges involved event hosted at the Twentieth National Conference with noisy, cluttered, and unstructured on Artificial Intelligence (AAAI 2005). The robot event had a particularly strong human environments. Scavenger Hunt: Autonomous robots were required to search a cluttered and crowded environment This year, AAAI changed the venue format for a defined list of objects and were from a convention center to a hotel setting. The Scavenger as defined by the team, and feedback Hunt event was organized by Douglas from the participants. Blank from Bryn Mawr College, the Robot Robot Challenge: Robots were required to attend Challenge and the Open Interaction Task were the conference autonomously, including organized by Ashley Stroupe from the Jet registering for the conference, navigating the Propulsion Laboratory, the research component conference hall, talking with attendees, and of the exhibition was organized by Magdalena answering questions.

This paper presents a new framework for anytime heuristic search where the task is to achieve as many goals as possible within the allocated resources. We show the inadequacy of traditional distance-estimation heuristics for tasks of this type and present alternative heuristics that are more appropriate for multiple-goal search. In particular, we introduce the marginal-utility heuristic, which estimates the cost and the benefit of exploring a subtree below a search node. We developed two methods for online learning of the marginal-utility heuristic. One is based on local similarity of the partial marginal utility of sibling nodes, and the other generalizes marginal-utility over the state feature space. We apply our adaptive and non-adaptive multiple-goal search algorithms to several problems, including focused crawling, and show their superiority over existing methods.

This article describes the virtual humans developed as part of the Mission Rehearsal Exercise project, a virtual reality-based training system. This project is an ambitious exercise in integration, both in the sense of integrating technology with entertainment industry content, but also in that we have joined a number of component technologies that have not been integrated before. This integration has not only raised new research issues, but it has also suggested some new approaches to difficult problems. We describe the key capabilities of the virtual humans, including task representation and reasoning, natural language dialogue, and emotion reasoning, and show how these capabilities are integrated to provide more human-level intelligence than would otherwise be possible.