This paper describes experiments on identifying the language of a single name in isolation or in a document written in a different language. A new corpus has been compiled and made available, matching names against languages. This corpus is used in a series of experiments measuring the performance of general language models and names-only language models on the language identification task. Conclusions are drawn from the comparison between using general language models and names-only language models and between identifying the language of isolated names and the language of very short document fragments. Future research directions are outlined.

Techniques for data-mining, latent semantic analysis, contextual search of databases, etc. have long ago been developed by computer scientists working on information retrieval (IR). Experimental scientists, from all disciplines, having to analyse large collections of raw experimental data (astronomical, physical, biological, etc.) have developed powerful methods for their statistical analysis and for clustering, categorising, and classifying objects. Finally, physicists have developed a theory of quantum measurement, unifying the logical, algebraic, and probabilistic aspects of queries into a single formalism. The purpose of this paper is twofold: first to show that when formulated at an abstract level, problems from IR, from statistical data analysis, and from physical measurement theories are very similar and hence can profitably be cross-fertilised, and, secondly, to propose a novel method of fuzzy hierarchical clustering, termed \textit{semantic distillation} -- strongly inspired from the theory of quantum measurement --, we developed to analyse raw data coming from various types of experiments on DNA arrays. We illustrate the method by analysing DNA arrays experiments and clustering the genes of the array according to their specificity.

Linear Temporal Logic (LTL) is widely used for defining conditions on the execution paths of dynamic systems. In the case of dynamic systems that allow for nondeterministic evolutions, one has to specify, along with an LTL formula f, which are the paths that are required to satisfy the formula. Two extreme cases are the universal interpretation A.f, which requires that the formula be satisfied for all execution paths, and the existential interpretation E.f, which requires that the formula be satisfied for some execution path. When LTL is applied to the definition of goals in planning problems on nondeterministic domains, these two extreme cases are too restrictive. It is often impossible to develop plans that achieve the goal in all the nondeterministic evolutions of a system, and it is too weak to require that the goal is satisfied by some execution. In this paper we explore alternative interpretations of an LTL formula that are between these extreme cases. We define a new language that permits an arbitrary combination of the A and E quantifiers, thus allowing, for instance, to require that each finite execution can be extended to an execution satisfying an LTL formula (AE.f), or that there is some finite execution whose extensions all satisfy an LTL formula (EA.f). We show that only eight of these combinations of path quantifiers are relevant, corresponding to an alternation of the quantifiers of length one (A and E), two (AE and EA), three (AEA and EAE), and infinity ((AE)* and (EA)*). We also present a planning algorithm for the new language that is based on an automata-theoretic approach, and study its complexity.

In this paper we present and evaluate a general framework for the design of truthful auctions for matching agents in a dynamic, two-sided market. A single commodity, such as a resource or a task, is bought and sold by multiple buyers and sellers that arrive and depart over time. Our algorithm, Chain, provides the first framework that allows a truthful dynamic double auction (DA) to be constructed from a truthful, single-period (i.e. static) double-auction rule. The pricing and matching method of the Chain construction is unique amongst dynamic-auction rules that adopt the same building block. We examine experimentally the allocative efficiency of Chain when instantiated on various single-period rules, including the canonical McAfee double-auction rule. For a baseline we also consider non-truthful double auctions populated with ``zero-intelligence plus"-style learning agents. Chain-based auctions perform well in comparison with other schemes, especially as arrival intensity falls and agent valuations become more volatile.

This paper describes a system capable of semi-automatically filling an XML template from free texts in the clinical domain (practice guidelines). The XML template includes semantic information not explicitly encoded in the text (pairs of conditions and actions/recommendations). Therefore, there is a need to compute the exact scope of conditions over text sequences expressing the required actions. We present in this paper the rules developed for this task. We show that the system yields good performance when applied to the analysis of French practice guidelines.

Real-time heuristic search methods are used by situated agents in applications that require the amount of planning per move to be independent of the problem size. Such agents plan only a few actions at a time in a local search space and avoid getting trapped in local minima by improving their heuristic function over time. We extend a wide class of real-time search algorithms with automatically-built state abstraction and prove completeness and convergence of the resulting family of algorithms. We then analyze the impact of abstraction in an extensive empirical study in real-time pathfinding. Abstraction is found to improve efficiency by providing better trading offs between planning time, learning speed and other negatively correlated performance measures.

Simulated annealing is a popular method for approaching the solution of a global optimization problem. Existing results on its performance apply to discrete combinatorial optimization where the optimization variables can assume only a finite set of possible values. We introduce a new general formulation of simulated annealing which allows one to guarantee finite-time performance in the optimization of functions of continuous variables. The results hold universally for any optimization problem on a bounded domain and establish a connection between simulated annealing and up-to-date theory of convergence of Markov chain Monte Carlo methods on continuous domains. This work is inspired by the concept of finite-time learning with known accuracy and confidence developed in statistical learning theory.

Hackman delivered a talk entitled "Humans, Robots, and Teams" that leveraged work in The conference's outstanding paper award went to "Humanoid Robots as a Passive-Social Medium: A Field Experiment at a Train Station" by Kotaro The best student paper award went to Guy Hoffman and Cynthia Breazeal for their paper, titled "Effects of Anticipatory HRI-2007 was the second step "Speed Adaptation for a Robot Walking Spurred by included teamwork, social robotics, momentum has been built for HRI-advances in robotics technologies and adaptation, observation and metrics, 2008, which will be held in Amsterdam, communications, many researchers attention, user experience, and The Netherlands, March 12-15, are studying how to use these field testing. The 21st International FLAIRS Conference (FLAIRS-21) will be held May 15 - 17, 2008 at the Grand Bay Miami Hotel in the village of Coconut Grove, Miami, Florida, USA. The conference hotel is on the waterfront of Biscayne Bay close to downtown Miami and South Beach. FLAIRS-21 will feature technical papers, special tracks, and General Chair invited speakers on artificial intelligence. Architectures: Agents and distributed AI, Intelligent user interfaces, Natural lane@ict.usc.edu

Symposia will be limited to between forty and sixty participants. Each participant will be expected to attend a single symposium. In addition to invited participants, a limited number of other interested parties will be allowed to register in each symposium on a first-come, first-served basis. Working notes will be prepared and distributed to participants in each symposium, but will not otherwise be available unless published as an AAAI Technical Report or edited collection. The final deadline for registration is October 12, 2007. For registration information, please contact AAAI at fss07@aaai.org or visit AAAI's web site (www.aaai.org/Symposia/Fall/fss07.

The infrastructure of modern society is controlled by software systems that are vulnerable to attacks. Many such attacks, launched by "recreational hackers" have already led to severe disruptions and significant cost. It, therefore, is critical that we find ways to protect such systems and to enable them to continue functioning even after a successful attack. This article describes AWDRAT, a prototype middleware system for providing survivability to both new and legacy applications. AWDRAT stands for architectural differencing, wrappers, diagnosis, recovery, adaptive software, and trust modeling. AWDRAT uses these techniques to gain visibility into the execution of an application system and to compare the application's actual behavior to that which is expected. In the case of a deviation, AWDRAT conducts a diagnosis that determines which computational resources are likely to have been compromised and then adds these assessments to its trust model. The trust model in turn guides the recovery process, particularly by guiding the system in its choice among functionally equivalent methods and resources.AWDRAT has been applied to and evaluated on an example application system, a graphical editor for constructing mission plans. We describe a series of experiments that were performed to test the effectiveness of AWDRAT in recognizing and recovering from simulated attacks, and we present data showing the effectiveness of AWDRAT in detecting a variety of compromises to the application system (approximately 90 percent of all simulated attacks are detected, diagnosed, and corrected). We also summarize some lessons learned from the AWDRAT experiments and suggest approaches for comprehensive application protection methods and techniques.