In this regard, the presentation of the three priority programs on agent technology, sponsored by the German Science Foundation (DFG), deserve special mention. André gave an Aachen, was the general chair. This description will transform the web into a workshops preceding the main conference. Except for the workshop on other things, how lazy unfolding of He spoke, among other things, about applications of description logics, concept definitions can dramatically ongoing efforts to develop a modeling fitting with the special focus of KIspeed up the computation of least framework for web services, 2002, all others were concerned with common subsumers in practice. Sponsored by: International Society of Applied Intelligence - Organized in Cooperation with: AAAI, ACM/SIGART, CSCSI/SCEIO, ECCAI, ENNS, INNS, JSAI, NRC, and SWT IEA/AIE-2004 continues the tradition of emphasizing applications of artificial intelligence and expert/knowledge-based systems to engineering and industrial problems as well as application of intelligent systems technology to solve real-life problems.

Successes and Challenges" by Alon Halevy, University of Washington; "Constraint Satisfaction, Santa Cruz; "Self-Reconfiguring Robots: Challenges and Successes" by Daniela Rus, Dartmouth University; "Automated Verification Graphs, Automata, and Logic" by Moshe Vardi, "Quantum Information: Fundamentals the world have gathered each summer One hundred the conference is always after conference hours. Also among this year's invited As part of the American Association As In addition to the strong technical to advance the science and practice part of a special track on AI and the track of the conference, the Fifteenth of AI, the organization continues web, Henzinger will discuss the future Innovative Applications of AI conference to play a leading role in organizing of search engines on the internet, (IAAI-03) will be collocated with and sponsoring these annual summer describing work under way to IJCAI. Through the years, we have conferences. Other invited talks include "Deploying in a broad range of computer systems, Information Agents on the machinery, and electronic devices Because AI is an umbrella term for a of Southern California; "Web However, where is the newest, most This book looks at some of the results of this synergy among AI, cognitive science, and education. Examples include virtual students whose misconceptions force students to reflect on their own knowledge, intelligent tutoring systems, and speech recognition technology that helps students learn to read.

This article reports on an extensive survey and analysis of research work related to machine learning as it applies to automated planning over the past 30 years. Major research contributions are broadly characterized by learning method and then descriptive subcategories. Survey results reveal learning techniques that have extensively been applied and a number that have received scant attention. We extend the survey analysis to suggest promising avenues for future research in learning based on both previous experience and current needs in the planning community.

In an attempt to solve as much of the AAAI Robot Challenge as possible, five research institutions representing academia, industry, and government integrated their research into a single robot named GRACE. This article describes this first-year effort by the GRACE team, including not only the various techniques each participant brought to GRACE but also the difficult integration effort itself.

Hence, no training phase is needed. The local statistics define an with white lines; goals are blue and yellow; and expectation of "how the two sides of the curve robots are black with light blue or magenta might look." Second, refine the estimation of model parameters These stringent rules allow for simple mechanisms by (1) updating the mean of the estimation for object detection and recognition: in a maximum a posteriori step such that Segment the captured image into blobs of the the vicinity of the curve matches the expectation same color and interpret these blobs. To the defined by the local statistics and (2) updating best of our knowledge, all autonomous robot the covariance of the estimation based on soccer teams with vision-based perception apply the Hessian of the resulting objective function. However, because The two steps are repeated until there is no the RoboCup committee is planning to significant change in the estimated Gaussian make the rules more realistic, these objectrecognition distribution.

The RoboCupJunior division of RoboCup is now entering its third year of international participation and is growing rapidly in size and popularity. This article first outlines the history of the junior league since it was first demonstrated in Paris at RoboCup-1998 and describes how it has evolved into the international sensation it is today. Although the popularity of the event is self-evident, we are working to identify and quantify the educational benefits of the initiative. The remainder of the article focuses on describing our efforts to encapsulate these qualities, highlighting results from a pilot study conducted at RoboCupJunior-2000 and presenting new data from a subsequent study of RoboCupJunior-2001.

Competitions were held at Since the first competition in 1997 (Kitano Fukuoka Dome Baseball Stadium from 19 to 23 1998), RoboCup has grown into an international June followed by the International RoboCup joint research project in which about Symposium on 24 to 25 June. It is one of RoboCup is an attempt to foster intelligent the most ambitious projects of the twenty-first robotics research by providing a standard century. RoboCup currently consists of three problem, the ultimate goal of which is to divisions: (1) RoboCupSoccer, a move toward build a team of 11 humanoid robots that the final goal; (2) RoboCupRescue, a serious social can beat the human World Cup champion application of rescue activities for any kind soccer team by 2050. It's obvious that of disaster; and (3) RoboCupJunior, an international building a robot to play a soccer game is an education-based initiative designed to immense challenge; readers might therefore introduce young students to robotics. It is our intention to use since 1997 and showed its epoch-making new RoboCup as a vehicle to promote robotics standard for future RoboCups. One thousand and AI research by offering a publicly appealing four team members from 188 teams from 30 but formidable challenge (Asada et nations around the world participated. It included al. 1999; Kitano et al. 1997). The humanoid league is a big challenge knowledge, this was the largest robotic event with a long-term, high-impact goal, which in history.

Natural language generation (NLG) systems are computer software systems that produce texts in English and other human languages, often from non-linguistic input data. NLG systems, like most AI systems, need substantial amounts of knowledge. However, our experience in two NLG projects suggests that it is difficult to acquire correct knowledge for NLG systems; indeed, every knowledge acquisition (KA) technique we tried had significant problems. In general terms, these problems were due to the complexity, novelty, and poorly understood nature of the tasks our systems attempted, and were worsened by the fact that people write so differently. This meant in particular that corpus-based KA approaches suffered because it was impossible to assemble a sizable corpus of high-quality consistent manually written texts in our domains; and structured expert-oriented KA techniques suffered because experts disagreed and because we could not get enough information about special and unusual cases to build robust systems. We believe that such problems are likely to affect many other NLG systems as well. In the long term, we hope that new KA techniques may emerge to help NLG system builders. In the shorter term, we believe that understanding how individual KA techniques can fail, and using a mixture of different KA techniques with different strengths and weaknesses, can help developers acquire NLG knowledge that is mostly correct.

Bayesian belief networks have grown to prominence because they provide compact representations for many problems for which probabilistic inference is appropriate, and there are algorithms to exploit this compactness. The next step is to allow compact representations of the conditional probabilities of a variable given its parents. In this paper we present such a representation that exploits contextual independence in terms of parent contexts; which variables act as parents may depend on the value of other variables. The internal representation is in terms of contextual factors (confactors) that is simply a pair of a context and a table. The algorithm, contextual variable elimination, is based on the standard variable elimination algorithm that eliminates the non-query variables in turn, but when eliminating a variable, the tables that need to be multiplied can depend on the context. This algorithm reduces to standard variable elimination when there is no contextual independence structure to exploit. We show how this can be much more efficient than variable elimination when there is structure to exploit. We explain why this new method can exploit more structure than previous methods for structured belief network inference and an analogous algorithm that uses trees.

Although many algorithms have been designed to construct Bayesian network structures using different approaches and principles, they all employ only two methods: those based on independence criteria, and those based on a scoring function and a search procedure (although some methods combine the two). Within the score+search paradigm, the dominant approach uses local search methods in the space of directed acyclic graphs (DAGs), where the usual choices for defining the elementary modifications (local changes) that can be applied are arc addition, arc deletion, and arc reversal. In this paper, we propose a new local search method that uses a different search space, and which takes account of the concept of equivalence between network structures: restricted acyclic partially directed graphs (RPDAGs). In this way, the number of different configurations of the search space is reduced, thus improving efficiency. Moreover, although the final result must necessarily be a local optimum given the nature of the search method, the topology of the new search space, which avoids making early decisions about the directions of the arcs, may help to find better local optima than those obtained by searching in the DAG space. Detailed results of the evaluation of the proposed search method on several test problems, including the well-known Alarm Monitoring System, are also presented.