ppxscal/embedding_network huggingface dataset:
Coordinating agile systems through the model-based execution of temporal plans
Authors: Thomas Léauté, Brian C. Williams
Venue: Proceedings of the 20th national conference on Artificial intelligence - Volume 1 (2005)

Agile autonomous systems are emerging, such as unmanned aerial vehicles (UAVs), that must robustly perform tightly coordinated time-critical missions; for example, military surveillance or search-and-rescue scenarios. In the space domain, execution of temporally flexible plans has provided an enabler for achieving the desired coordination and robustness. We address the challenge of extending plan execution to underactuated systems that are controlled indirectly through the setting of continuous state variables. Our solution is a novel model-based executive that takes as input a temporally flexible state plan, specifying intended state evolutions, and dynamically generates a near-optimal control sequence. To achieve optimality and safety, the executive plans into the future, framing planning as a disjunctive programming problem. To achieve robustness to disturbances and tractability, planning is folded within a receding horizon, continuous planning framework. Key to performance is a problem reduction method based on constraint pruning. We benchmark performance through a suite of UAV scenarios using a hardware-in-the-loop testbed.
Trail Patterns in Social Tagging Systems: Role of Tags as Digital Pheromones
Authors: Thomas George Kannampallil, Wai-Tat Fu
Venue: Proceedings of the 5th International Conference on Foundations of Augmented Cognition. Neuroergonomics and Operational Neuroscience: Held as Part of HCI International 2009 (2009)

The popularity of social information systems has been driven by their ability to help users manage, organize and share online resources. Though the research exploring the use of tags is relatively new, two things are widely acknowledged in the research community: (a) tags act as a medium for social collaboration, navigation and browsing and (b) an overall stable equilibrium exists among tag patterns due to the social nature of the tagging process. But there is very little agreement on what causes these stable patterns. In this paper, we take an evolutionary perspective to understand the process of tagging to investigate whether tags act as "way finders" or digital pheromones in social tagging systems. We investigate the existence of tag trails based on a semantic similarity measure among existing tags. We found that over 50% of the resources we evaluated exhibited strong trail patterns. The implications of these patterns for the design and management of social tagging systems is discussed.
Decidable reasoning in terminological knowledge representation systems
Authors: Martin Buchheit, Francesco M. Donini, Andrea Schaerf
Venue: Journal of Artificial Intelligence Research (1993)

Terminological knowledge representation systems (TKRSs) are tools for designing and using knowledge bases that make use of terminological languages (or concept languages). We analyze from a theoretical point of view a TKRS whose capabilities go beyond the ones of presently available TKRSs. The new features studied, often required in practical applications, can be summarized in three main points. First, we consider a highly expressive terminological language, called ALCNR, including general complements of concepts, number restrictions and role conjunction. Second, we allow to express inclusion statements between general concepts, and terminological cycles as a particular case. Third, we prove the decidability of a number of desirable TKRS-deduction services (like satisfiability, subsumption and instance checking) through a sound, complete and terminating calculus for reasoning in ALCNR-knowledge bases. Our calculus extends the general technique of constraint systems. As a byproduct of the proof, we get also the result that inclusion statements in ALCNR can be simulated by terminological cycles, if descriptive semantics is adopted.
PYTHON 2.6 and C or C++: Extending and Embedding Python
Authors: Guido van Rossum, Fred L. Drake
Venue:  (2009)

PYTHON 2.6 and C or C++, Extending and Embedding Python (Python documentation MANUAL Part 5). This is a printed edition of the official Python documentation from the PYTHON 2.6.1 distribution. For each copy sold $1 will be donated to the PYTHON SOFTWARE FOUNDATION by the publisher. This book is part of a six-part series of PYTHON 2.6 documentation. Searching for "Python Documentation Manual" will show all six available books as well as the series of Python 3.0 documentation books. THE AUTHOR Guido van Rossum, is the inventor of Python. Fred L. Drake, Jr. is the official editor of the Python documentation.
Mobile Agent-Based Data Gathering for Web Image Retrieval
Authors: Ruhan He, Yong Zhu, Naixue Xiong, Wei Zhan, Yanjun Zhao
Venue: Proceedings of the 2009 International Conference on Computational Science and Engineering - Volume 02 (2009)

A mobile agent based data gathering system for Web image retrieval is proposed in this paper. In our system, the data gathering system are implemented as mobile agents that can run on the remote servers, which lead to most computing intensive tasks, i.e. feature extracting, indexing , can be parallelized and carried out on different remote web servers. It makes a great improvement in processing speed by multiple mobile agents cooperatively executing computing intensive tasks on different servers. Moreover, it decreases network traffic obviously because only necessary processing results needs to be transferred among different servers. The data gathering system is applied in VAST system and the experimental results demonstrates its effectiveness.
Optimal Scheduling of Two Communication Flows on Multiple Disjoint Packet-Type Aware Paths
Authors: Mugurel Ionut Andreica, Nicolae Tapus
Venue: Proceedings of the 2008 10th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (2008)

Communication flows in distributed systems often present a poor performance, because they are unaware of each other and end up competing for the same bottleneck resources. A solution to this problem consists of scheduling the communication flows in order to optimize some performance metric. In this paper we study the scheduling of two communication flows over multiple disjoint paths, such that the maximum completion time (makespan) is minimized. Each flow is composed of a large number of identical packets of the same type. The paths are aware of the packet types and have different transmission times for each type. We consider the objectives of minimizing the makespan and the weighted sum of completion times. We also consider some error-correcting issues, as well as the possibility of dropping the packet ordering constraints.
Utility Dependence in Correct and Fair Rational Secret Sharing
Authors: Gilad Asharov, Yehuda Lindell
Venue: Proceedings of the 29th Annual International Cryptology Conference on Advances in Cryptology (2009)

The problem of carrying out cryptographic computations when the participating parties are rational in a game-theoretic sense has recently gained much attention. One problem that has been studied considerably is that of rational secret sharing. In this setting, the aim is to construct a mechanism (protocol) so that parties behaving rationally have incentive to cooperate and provide their shares in the reconstruction phase, even if each party prefers to be the only one to learn the secret.Although this question was only recently asked by Halpern and Teague (STOC 2004), a number of works with beautiful ideas have been presented to solve this problem. However, they all have the property that the protocols constructed need to know the actual utility values of the parties (or at least a bound on them). This assumption is very problematic because the utilities of parties are not public knowledge. We ask whether this dependence on the actual utility values is really necessary and prove that in the basic setting, rational secret sharing cannot be achieved without it. On the positive side, we show that by somewhat relaxing the standard assumptions on the utility functions, it is possible to achieve utility independence. In addition to the above, observe that the known protocols for rational secret sharing that do not assume simultaneous channels all suffer from the problem that one of the parties can cause the others to output an incorrect value. (This problem arises when a party gains higher utility by having another output an incorrect value than by learning the secret itself; we argue that such a scenario is not at all unlikely.) We show that this problem is inherent in the non-simultaneous channels model, unless the actual values of the parties' utilities from this attack is known, in which case it is possible to prevent this from happening.
A Hybrid Method of Multidimensional Scaling and Clustering for Determining Genetic Influence on Phenotypes
Authors: Qiao Li, Wenjia Wang, Alexander J. Macgregor, George Smith
Venue: Proceedings of the 5th International Conference on Advanced Data Mining and Applications (2009)

As a branch of modern biomedical study, genetic epidemiology research on complex diseases usually aims to identify the genetic influences on phenotypes. This paper presents a hybrid method named MDS-C, which combines the multidimensional scaling method and a clustering algorithm, to unveil the genetic relationships among phenotypes by using phenotypic information only. In MDS-C, the cross-twin cross-trait correlation between any two phenotypes is designed to measure the genetic similarity. MDS-C is verified by a series of simulation studies. Then it is applied to a real bone mineral density (BMD) dataset collected by the St Thomas' UK Adult Twin Registry. Its results suggest that the genetic influence on BMD is site-specific.
Automatically assessing review helpfulness
Authors: Soo-Min Kim, Patrick Pantel, Tim Chklovski, Marco Pennacchiotti
Venue: Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing (2006)

User-supplied reviews are widely and increasingly used to enhance e-commerce and other websites. Because reviews can be numerous and varying in quality, it is important to assess how helpful each review is. While review helpfulness is currently assessed manually, in this paper we consider the task of automatically assessing it. Experiments using SVM regression on a variety of features over Amazon.com product reviews show promising results, with rank correlations of up to 0.66. We found that the most useful features include the length of the review, its unigrams, and its product rating.
A Web Service Composition Method Based on Interface Matching
Authors: Tao He, Huaikou Miao, Liping Li
Venue: Proceedings of the 2009 Eigth IEEE/ACIS International Conference on Computer and Information Science (2009)

This paper proposes an automatic Web service composition method which considers both services’ input/output type compatibility and behavioral constraint compatibility based on Petri Nets to raise the composition reliability. It presents a novel technique for discovering semantic relations between pre and post-conditions of different services using their ontological descriptions. The technique takes semantic similarity of pre and post-conditions into account and builds on work discovering semantic relationships between interfaces (input and output) of Web services. An algorithm is presented for obtaining the Petri net models of the composite Web services which satisfy not only the user’s input/output requirements but also the user’s behavioral constraints. It also analyzes the service dependencies and the complexity of OWL-S services tasks.
Nash Bargaining Based Ad Networks for Sponsored Search Auctions
Authors: Ramakrishnan Kannan, Dinesh Garg, Karthik Subbian, Y. Narahari
Venue: Proceedings of the 2009 IEEE Conference on Commerce and Enterprise Computing (2009)

In this paper, we consider an emerging scenario in sponsored web search auctions where ad networks would be involved as intermediaries between a search engine and its advertisers. In this context, we address the problem of the ad network identifying a bid profile that makes the sponsored search auction attractive to the registered bidders. Given (1) the valuation of the advertisers competing for sponsored slots corresponding to a keyword, and (2) relevant click-through rates, the proposed algorithm generates a bid profile that can be input to a standard generalized second price based sponsored search auction mechanism. The bid profile is derived using a two person Nash bargaining model which ensures a fair share of utility between the search engine and the advertisers. In the proposed model, the auctioneer (search engine) is one player and a virtual aggregated bidder representing all the $n$ advertisers is the other player. We show that the feasible set for the Nash bargaining formulation is a convex hull with three points that can be computed in $O(nlogn)$ time. We derive the Nash bargaining solution and show that it can be mapped to a bid profile of the bidders in $O(n)$ time.
Analysis of strategic knowledge in back of the envelope reasoning
Authors: Praveen K. Paritosh, Kenneth D. Forbus
Venue: Proceedings of the 20th national conference on Artificial intelligence - Volume 2 (2005)

Back of the envelope (BotE) reasoning involves generating quantitative answers in situations where exact data and models are unavailable and where available data is often incomplete and/or inconsistent. A rough estimate generated quickly is more valuable and useful than a detailed analysis, which might be unnecessary, impractical, or impossible because the situation does not provide enough time, information, or other resources to perform one. Such reasoning is a key component of commonsense reasoning about everyday physical situations. We present an implemented system, BotE-Solver, that can solve about a dozen estimation questions like "What is the annual cost of healthcare in USA?" from different domains using a library of strategies and the Cyc knowledge base. BotE-Solver is a general-purpose problem solving framework that uses strategies represented as suggestions, and keeps track of problem solving progress in an AND/OR tree. A key contribution of this paper is a knowledge level analysis [Newell, 1982] of the strategic knowledge used in BotE reasoning. We present a core collection of seven powerful estimation strategies that provides broad coverage for such problem solving. We hypothesize that this is the complete set of back of the envelope problem solving strategies. We present twofold support for this hypothesis: 1) an empirical analysis of all problems (n=44) on Force and Pressure, Rotation and Mechanics, Heat, and Astronomy from Clifford Swartz's "Back-of-the-Envelope Physics" [Swartz, 2003], and 2) an analysis of strategies used by BotE-Solver.
Applying Real Time Physiological Measures of Cognitive Load to Improve Training
Authors: Joseph T. Coyne, Carryl Baldwin, Anna Cole, Ciara Sibley, Daniel M. Roberts
Venue: Proceedings of the 5th International Conference on Foundations of Augmented Cognition. Neuroergonomics and Operational Neuroscience: Held as Part of HCI International 2009 (2009)

This paper discusses how the fields of augmented cognition and neuroergonomics can be expanded into training. Several classification algorithms based upon EEG data and occular data are discussed in terms of their ability to classify operator state in real time. These indices have been shown to enhance operator performance within adaptive automation paradigms. Learning is different from performing a task that one is familiar with. According to cognitive load theory (CLT), learning is essentially the act of organizing information from working memory into long term memory. However, our working memory system has a bottleneck in this process, such that when training exceeds working memory capacity, learning is hindered. This paper discusses how CLT can be combined with multiple resource theory to create a model of adaptive training. This new paradigm hypothesizes that a system that can monitor working memory capacity in real time and adjust training difficulty can improve learning.
Exploiting semantic information for manual anaphoric annotation in Cast3LB corpus
Authors: Borja Navarro, Rubén Izquierdo, Maximiliano Saiz-Noeda
Venue: Proceedings of the 2004 ACL Workshop on Discourse Annotation (2004)

This paper presents the discourse annotation followed in Cast3LB, a Spanish corpus annotated with several information sources (morphological, syntactic, semantic and coreferential) at syntactic, semantic and discourse level. 3LB annotation scheme has been developed for three languages (Spanish, Catalan and Basque). Human annotators have used a set of tagging techniques and protocols. Several tools have provided them with a friendly annotation scheme. At discourse level, anaphoric and coreference expressions are annotated. One of the most interesting contributions to this annotation scenario is the enriched anaphora resolution module that is based on the previously defined semantic annotation phase to expand the discourse information and use it to suggest the correct antecedent of an anaphora to the annotator. This paper describes the relevance of the semantic tags in the discourse annotation in Spanish corpus Cast3LB and shows both levels and tools in the mentioned discourse annotation scheme.
Prisoner's Dilemma Game on Network
Authors: Masahiro Ono, Mitsuru Ishizuka
Venue: Multi-Agent Systems for Society: 8th Pacific Rim International Workshop on Multi-Agents, PRIMA 2005, Kuala Lumpur, Malaysia, September 26-28, 2005, Revised Selected Papers (2009)

We study on the Prisoner's Dilemma game on network to clarify the influence of the network structures on agent strategies, and vice versa. A model is proposed to treat an interaction between the agent strategies and the network formation process. In case of a fixed network, it is observed that the distribution as well as the propagation speed of an agent strategy depends on the network structure. In an experiment combining the agent evolution and the network formation, a novel network that has a few agents connected by all of other agents appears.
Detection and estimation of the motion velocity vector of a inhomogeneous spatially extended object by image. II
Authors: R. V. Kutsov, A. P. Trifonov
Venue: Automation and Remote Control (2009)

Basing on the properties of the logarithm of likelihood ratio functional found in [1], we obtain asymptotic expressions for characteristics of detection and estimation of the motion velocity vector of an inhomogeneous spatially extended object.
Verifying Component-Based Software: Deep Mathematics or Simple Bookkeeping?
Authors: Jason Kirschenbaum, Bruce Adcock, Derek Bronish, Hampton Smith, Heather Harton, Murali Sitaraman, Bruce W. Weide
Venue: Proceedings of the 11th International Conference on Software Reuse: Formal Foundations of Reuse and Domain Engineering (2009)

Anecdotal experience constructing proofs of correctness of code built from reusable software components reveals that they tend to be relatively trivial bookkeeping exercises: they rarely require a substantive mathematical deduction. A careful empirical analysis of hundreds of verification conditions (VCs) for a library of component-client code shows the level of sophistication each proof requires, and suggests how to use the results to characterize a notion of mathematical "obviousness."
Optimal Sherali-Adams Gaps from Pairwise Independence
Authors: Konstantinos Georgiou, Avner Magen, Madhur Tulsiani
Venue: Proceedings of the 12th International Workshop and 13th International Workshop on Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (2009)

This work considers the problem of approximating fixed predicate constraint satisfaction problems (MAX k-CSP(P)). We show that if the set of assignments accepted by P contains the support of a balanced pairwise independent distribution over the domain of the inputs, then such a problem on n variables cannot be approximated better than the trivial (random) approximation, even using ¿(n) levels of the Sherali-Adams LP hierarchy.It was recently shown [3] that under the Unique Game Conjecture, CSPs with predicates with this condition cannot be approximated better than the trivial approximation. Our results can be viewed as an unconditional analogue of this result in the restricted computational model defined by the Sherali-Adams hierarchy. We also introduce a new generalization of techniques to define consistent "local distributions" over partial assignments to variables in the problem, which is often the crux of proving lower bounds for such hierarchies.
Hierarchical Graph Rewriting as a Unifying Tool for Analyzing and Understanding Nondeterministic Systems
Authors: Kazunori Ueda, Takayuki Ayano, Taisuke Hori, Hiroki Iwasawa, Seiji Ogawa
Venue: Proceedings of the 6th International Colloquium on Theoretical Aspects of Computing (2009)

We have designed and implemented LMNtal (pronounced "elemental"), a language based on hierarchical graph rewriting that allows us to encode diverse computational models involving concurrency, mobility and multiset rewriting. Towards its novel applications, the system has recently evolved into a model checker that employs LMNtal as the modeling language and PLTL as the specification language. The strengths of our LMNtal model checker are its powerful data structure, highly nondeterministic computation it can express, and virtually no discrepancy between programming and modeling languages. Models expressed in Promela, MSR, and Coloured Petri Nets can be easily encoded into LMNtal. The visualizer of the LMNtal IDE turned out to be extremely useful in understanding models by state space browsing. The LMNtal IDE has been used to run and visualize diverse examples taken from the fields of model checking, concurrency and AI search.
A Robust Iris Localization Model Based on Phase Congruency and Least Trimmed Squares Estimation
Authors: Lili Pan, Mei Xie, Tao Zheng, Jianli Ren
Venue: Proceedings of the 15th International Conference on Image Analysis and Processing (2009)

Iris localization is a crucial step in iris recognition. The previous proposed algorithms perform unsatisfactorily due to the disturbing of eyelash and variation of image brightness. To solve these problems, we proposed a robust iris position estimation algorithm based on phase congruency analysis and LTSE (Least Trimmed Squares Estimation). Through using the robust regression method to fit iris edge points we can solve the eyelash occlusion problem at a certain extent. The experimental results demonstrate the validity of this algorithm.
RBF Neural Network Adaptive Control of Microturbine
Authors: Yan Shijie, Wang Xu
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 02 (2009)

Microturbine generator (MTG) system is a clean, efficient, low cost and novel energy supply system and it is widely used in a variety of power generation and industrial applications. MTG dynamics are often complex and vary with operating point and ambient conditions, although the relationship of input-output is very simple, therefore conventional control law adopted cannot achieve expectant result. A novel single neuron adaptive control algorithm is proposed in combining with PID, based on radial basis function (RBF) neural network on-line identification. Through adjusting control parameter on-line, excellent flexibility and adaptability as well as high precision and good robustness can be achieved. The algorithm has been applied in "100kW microturbine control and power converter system". The results of simulation are shown that the algorithm is very valid.