We present in this paper a first-order axiomatization of an extended theory $T$ of finite or infinite trees, built on a signature containing an infinite set of function symbols and a relation $\fini(t)$ which enables to distinguish between finite or infinite trees. We show that $T$ has at least one model and prove its completeness by giving not only a decision procedure, but a full first-order constraint solver which gives clear and explicit solutions for any first-order constraint satisfaction problem in $T$. The solver is given in the form of 16 rewriting rules which transform any first-order constraint $\phi$ into an equivalent disjunction $\phi$ of simple formulas such that $\phi$ is either the formula $\true$ or the formula $\false$ or a formula having at least one free variable, being equivalent neither to $\true$ nor to $\false$ and where the solutions of the free variables are expressed in a clear and explicit way. The correctness of our rules implies the completeness of $T$. We also describe an implementation of our algorithm in CHR (Constraint Handling Rules) and compare the performance with an implementation in C++ and that of a recent decision procedure for decomposable theories.

This paper is a survey of a large number of informal definitions of ``intelligence'' that the authors have collected over the years. Naturally, compiling a complete list would be impossible as many definitions of intelligence are buried deep inside articles and books. Nevertheless, the 70-odd definitions presented here are, to the authors' knowledge, the largest and most well referenced collection there is.

This paper is concerned with a class of algorithms that perform exhaustive search on propositional knowledge bases. We show that each of these algorithms defines and generates a propositional language. Specifically, we show that the trace of a search can be interpreted as a combinational circuit, and a search algorithm then defines a propositional language consisting of circuits that are generated across all possible executions of the algorithm. In particular, we show that several versions of exhaustive DPLL search correspond to such well-known languages as FBDD, OBDD, and a precisely-defined subset of d-DNNF. By thus mapping search algorithms to propositional languages, we provide a uniform and practical framework in which successful search techniques can be harnessed for compilation of knowledge into various languages of interest, and a new methodology whereby the power and limitations of search algorithms can be understood by looking up the tractability and succinctness of the corresponding propositional languages.

By early July, each paper had been assigned to one supervisor SPC member and one PC member. The algorithm recorded the justifications for each assignment in terms of the specific bid and keyword match. When completed, the reviews were and Its Benefits to Society." The tutorial program was Hyderabad, India, January 6-12, 2007. At the chaired by Cynthia Braezeal. More The theme of the conference was "AI Figure 2 shows the distribution of their course work.

Summer calendar of AI events.

Approximately November 9-11, at the Westin Arlington and IAAI-08, please see www.aaai.org/

The Dialogue on Dialogues workshop was organized as a satellite event at the Interspeech 2006 conference in Pittsburgh, Pennsylvania, and it was held on September 17, 2006, immediately before the main conference. It was planned and coordinated by Michael McTear (University of Ulster, UK), Kristiina Jokinen (University of Helsinki, Finland), and James A. Larson (Portland State University, USA). The one-day workshop involved more than 40 participants from Europe, the United States, Australia, and Japan.

Will we see autonomous humanoid robots that play (and win) soccer against the human soccer world champion in the year 2050? This question is not easy to answer, and the idea is quite visionary. However, this is the goal of the RoboCup Federation. There are serious research questions that have to be tackled behind the scenes of a soccer game: perception, decision making, action selection, hardware design, materials, energy, and more. RoboCup is also about the nature of intelligence, and playing soccer acts as a performance measure of systems that contain artificial intelligence -- in much the same way chess has been used over the last century. This article outlines the current situation following 10 years of research with reference to the results of the 2006 World Championship in Bremen, Germany, and discusses future challenges.

Conversational dialogue is an oft-cited example of mixed-initiative interaction, referring to the ability of each participant in a dialogue to take initiative to guide or add to a discussion. Endowing an automated dialogue system communicate, and coordinate with with the ability both to take initiative ("What In the course like to add a side trip.") However, of efforts to achieve goals while immersed mixed-initiative interaction extends beyond in shared context. We continue to engage spoken conversations to include a broad spectrum one another in efficient, tightly woven of collaborative problem solving marked collaborations, reasoning with remarkable efficiency by an interleaving of contributions by different about the beliefs, preferences, intentions, participants. Mastering mixed-initiative interaction poses The inferences underlying successful collaborations a constellation of fascinating challenges and typically stream in such an effortless opportunities for AI researchers.

Mixed-initiative assistants are agents that interact seamlessly with humans to extend their problem-solving capabilities or provide new capabilities. Developing such agents requires the synergistic integration of many areas of AI, including knowledge representation, problem solving and planning, knowledge acquisition and learning, multiagent systems, discourse theory, and human-computer interaction. This paper introduces seven aspects of mixed-initiative reasoning (task, control, awareness, communication, personalization, architecture, and evaluation) and discusses them in the context of several state-of-the-art mixed-initiative assistants. The goal is to provide a framework for understanding and comparing existing mixed-initiative assistants and for developing general design principles and methods.