The problem of maximum-likelihood (ML) estimation of discrete tree-structured distributions is considered. Chow and Liu established that ML-estimation reduces to the construction of a maximum-weight spanning tree using the empirical mutual information quantities as the edge weights. Using the theory of large-deviations, we analyze the exponent associated with the error probability of the event that the ML-estimate of the Markov tree structure differs from the true tree structure, given a set of independently drawn samples. By exploiting the fact that the output of ML-estimation is a tree, we establish that the error exponent is equal to the exponential rate of decay of a single dominant crossover event. We prove that in this dominant crossover event, a non-neighbor node pair replaces a true edge of the distribution that is along the path of edges in the true tree graph connecting the nodes in the non-neighbor pair. Using ideas from Euclidean information theory, we then analyze the scenario of ML-estimation in the very noisy learning regime and show that the error exponent can be approximated as a ratio, which is interpreted as the signal-to-noise ratio (SNR) for learning tree distributions. We show via numerical experiments that in this regime, our SNR approximation is accurate.

So, we have a variety of people here with different interests and backgrounds that I asked to talk about not just the key challenges ahead but potential opportunities and promising pathways, trajectories to solving those problems, and their predictions about how R&D might proceed in terms of the timing of various kinds of development over time. I asked the panelists briefly to frame their comments sharing a little bit about fundamental questions, such as, "What is the research goal?" Not everybody stays up late at night hunched over a computer or a simulation or a robotic system, pondering the foundations of intelligence and human-level AI. We have here today Lise Getoor from the University ipate the liability and insurance industry; and the of Maryland; Devika Subramanian, who other one, that it was a human interface problem, comes to us from Rice University; we have Carlos that people don't necessarily want to go and type Guestrin from Carnegie Mellon University (CMU); a bunch of yes/no questions into a computer to get James Hendler from Rensselaer Polytechnic Institute an answer, even with a rule-based explanation, (RPI); Mike Wellman at the University of that if you'd taken that just a step further and Michigan; Henry Kautz at tjhe University of solved the human problem, it might have worked. Rochester; and Joe Konstan, who comes to us from Related to that, I was remembering a bunch of the Midwest, as our Minneapolis person here on these smart house projects. And I have to admit I the panel. I think everyone Joe Konstan: I was actually surprised when you hates smart spaces. I think of myself at the core there's nobody there, do you warn people and give in human-computer interaction. So I went back them a chance to answer? There's no good answer and started looking at what I knew of artificial to this question. I can tell you if that person is in intelligence to try to see where the path forward bed asleep, the answer is no, don't wake them up was, and I was inspired by the past.

AAAI/SIGART Doctoral Consortium, and the second AAAI Educational Advances in Artificial Intelligence Symposium, to name only a few of the AAAI is pleased to present the 2011 Spring Symposium Series, to highlights. For complete information be held Monday through Wednesday, March 21-23, 2011, at on these programs, including Tutorial Stanford University.

On Tuesday morning, July 12, the program chairs will welcome attendees, and conference and AAAI awards will be presented. The awards ceremony will be followed by the AAAI-10 keynote address, to be include 199 oral presentations in the is the definitive point of interaction delivered by Leslie Pack Kaelbling main track, as well as 75 additional between entertainment software developers (Massachusetts Institute of Technology) presentations in the special tracks on interested in AI and academic entitled "Intelligent Interaction Bioinformatics, AI and the Web, Challenges and industrial AI researchers. AAAI-10 has an in AI, Integrated Intelligence, by AAAI, the conference is targeted outstanding program of invited presentations, Physically Grounded AI, Nectar, and at both the research and featuring Carla P. Gomes Senior Member, as well as poster presentations commercial communities, promoting (Cornell University), Barry O'Sullivan by a select number of exceptional AI research and practice in the context (University College Cork), David C. technical papers, short papers, of interactive digital entertainment Parkes (Harvard University), and student abstracts, and doctoral systems with an emphasis on commercial Michael Thielscher (The University of consortium abstracts. Registration information with Jay M. Tenenbaum (CollabRx The week is filled with a host of and other program details will Inc.), the 2010 recipient of the other programs, including the AI be available on the AIIDE-10 website Robert S. Engelmore Memorial Lecture Video Competition, the AI Poker at www.aaai.org/aiide10 The IAAI-10 program Semantic Robot Vision Challenge, the Michael Youngblood (University of will also feature talks by Majd Alwan General Game Playing Competition, North Carolina Charlotte). Care Empowered by Applied AI," Registration for AAAI-10, IAAI-10, and Vernor Vinge (San Diego State and EAAI-10 is included in one joint University) on "Species of Mind." fee.

Process integrated mechanisms (PIM) offer a new approach to the problem of coordinating the activity of physically distributed systems or devices. Current approaches to coordination all have well-recognized strengths and weaknesses. We propose a novel architecture to add to the mix, called the Process Integrated Mechanism (PIM), which enjoys the advantages of having a single controlling authority while avoiding the structural difficulties that have traditionally led to its rejection in many complex settings. In many situations, PIMs improve on previous models with regard to coordination, security, ease of software development, robustness and communication overhead. In the PIM architecture, the components are conceived as parts of a single mechanism, even when they are physically separated and operate asynchronously. The PIM models offers promise as an effective infrastructure for handling tasks that require a high degree of time-sensitive coordination between the components, as well as a clean mechanism for coordinating the high-level goals of loosely coupled systems. PIM models enable coordination without the fragility and high communication overhead of centralized control, but also without the uncertainty associated with the system-level behavior of a MAS.The PIM model provides an ease of programming with advantages over both multi-agent sys-tems and centralized architectures. It has the robustness of a multi-agent system without the significant complexity and overhead required for inter-agent communication and negotiation. In contrast to centralized approaches, it does not require managing the large amounts of data that the coordinating process needs to compute a global view. In a PIM, the process moves to the data and may perform computations on the components where the data is locally available, sharing only the information needed for coordination of the other components. While there are many remaining research issues to be addressed, we believe that PIMs offer an important and novel tech-nique for the control of distributed systems.

As microblogging grows in popularity, services like Twitter are coming to support information gathering needs above and beyond their traditional roles as social networks. But most users’ interaction with Twitter is still primarily focused on their social graphs, forcing the often inappropriate conflation of “people I follow” with “stuff I want to read.” We characterize some information needs that the current Twitter interface fails to support, and argue for better representations of content for solving these challenges. We present a scalable implementation of a partially supervised learning model (Labeled LDA) that maps the content of the Twitter feed into dimensions. These dimensions correspond roughly to substance, style, status, and social characteristics of posts. We characterize users and tweets using this model, and present results on two information consumption oriented tasks.

This article introduces the challenge of digital preservation in the area of engineering design and manufacturing and presents a methodology to apply knowledge representation and semantic techniques to develop Digital Engineering Archives. This work is part of an ongoing, multiuniversity, effort to create cyber infrastructure-based engineering repositories for undergraduates (CIBER-U) to support engineering design education. The technical approach is to use knowledge representation techniques to create formal models of engineering data elements, workflows and processes. With these formal engineering knowledge and processes can be captured and preserved with some guarantee of long-term interpretability. The article presents examples of how the techniques can be used to encode specific engineering information packages and workflows. These techniques are being integrated into a semantic wiki that supports the CIBER-U engineering education activities across nine universities and involving over 3500 students since 2006.

The development of intelligent environments is considered an important step toward the realization of the ambient intelligence vision. Greece, served as program chairs. The previous four editions of the IE conference have been held at the University of Essex, UK (in 2005), at the National Technical University of Athens, Greece (in 2006), at the University of Ulm, Germany (in 2007), and at the University of Washington campus in Seattle, Washington, USA (in 2008). The development of intelligent environments is About 120 delegates attended the workshops considered the first and primary step toward the and the conference. These included representatives realization of the ambient intelligence vision.

ICWSM-09 will feature two keynote to education and teaching.

In this paper after short review of the CSIEC project initialized by us in 2003 we present the continuing development and improvement of the CSIEC project in details, including the design of five new Microsoft agent characters representing different virtual chatting partners and the limitation of simulated dialogs in specific practical scenarios like graduate job application interview, then briefly analyze the actual conditions and features of its application field: web-based Englis h education in China. Finally we introduce our effort s to adapt this system to the requirements of English te aching and learning in China and point out the work next to do.