ppxscal/embedding_network huggingface dataset:
Facing the challenge of human-agent negotiations via effective general opponent modeling
Authors: Yinon Oshrat, Raz Lin, Sarit Kraus
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 1 (2009)

Automated negotiation agents capable of negotiating efficiently with people must deal with the fact that people are diverse in their behavior and each individual might negotiate in a different manner. Thus, automated agents must rely on a good opponent modeling component to model their counterpart and adapt their behavior to their partner. In this paper we present the KBAgent. The KBAgent is an automated negotiator that negotiates with each person only once, and uses past negotiation sessions of others as a knowledge base for general opponent modeling. The database is used to extract the likelihood of acceptance and proposals that may be offered by the opposite side. Experiments conducted with people show that the KBAgent negotiates efficiently with people and even achieves better utility values than another automated negotiator, shown to be efficient in negotiations with people. Moreover, the KBAgent achieves significantly better agreements, in terms of individual utility, than the human counterparts playing the same role.
Use of raster-based data layers to model spatial variation of seismotectonic data in probabilistic seismic hazard assessment
Authors: Mohammad R. Zolfaghari
Venue: Computers Geosciences (2009)

Recent achievements in computer and information technology have provided the necessary tools to extend the application of probabilistic seismic hazard mapping from its traditional engineering use to many other applications. Examples for such applications are risk mitigation, disaster management, post disaster recovery planning and catastrophe loss estimation and risk management. Due to the lack of proper knowledge with regard to factors controlling seismic hazards, there are always uncertainties associated with all steps involved in developing and using seismic hazard models. While some of these uncertainties can be controlled by more accurate and reliable input data, the majority of the data and assumptions used in seismic hazard studies remain with high uncertainties that contribute to the uncertainty of the final results. In this paper a new methodology for the assessment of seismic hazard is described. The proposed approach provides practical facility for better capture of spatial variations of seismological and tectonic characteristics, which allows better treatment of their uncertainties. In the proposed approach, GIS raster-based data models are used in order to model geographical features in a cell-based system. The cell-based source model proposed in this paper provides a framework for implementing many geographically referenced seismotectonic factors into seismic hazard modelling. Examples for such components are seismic source boundaries, rupture geometry, seismic activity rate, focal depth and the choice of attenuation functions. The proposed methodology provides improvements in several aspects of the standard analytical tools currently being used for assessment and mapping of regional seismic hazard. The proposed methodology makes the best use of the recent advancements in computer technology in both software and hardware. The proposed approach is well structured to be implemented using conventional GIS tools.
Analytic moment-based Gaussian process filtering
Authors: Marc Peter Deisenroth, Marco F. Huber, Uwe D. Hanebeck
Venue: Proceedings of the 26th Annual International Conference on Machine Learning (2009)

We propose an analytic moment-based filter for nonlinear stochastic dynamic systems modeled by Gaussian processes. Exact expressions for the expected value and the covariance matrix are provided for both the prediction step and the filter step, where an additional Gaussian assumption is exploited in the latter case. Our filter does not require further approximations. In particular, it avoids finite-sample approximations. We compare the filter to a variety of Gaussian filters, that is, the EKF, the UKF, and the recent GP-UKF proposed by Ko et al. (2007).
Zooming, multiple windows, and visual working memory
Authors: Matthew Plumlee, Colin Ware
Venue: Proceedings of the working conference on Advanced visual interfaces (2002)

Zooming and multiple windows are two techniques designed to address the focus-in-context problem. We present a theoretical model of performance that models the relative benefits of these techniques when used by humans for completing a task involving comparisons between widely separated groups of objects. The crux of the model is its cognitive component: the strength of multiple windows comes in the way they aid visual working memory. The task to which we apply our model is multiscale comparison, in which a user begins with a known visual pattern and searches for an identical or similar pattern among distracters. The model predicts that zooming should be better for navigating between a few distant locations when demands on visual memory are low, but that multiple windows are more efficient when demands on visual memory are higher, or there are several distant locations that must be investigated. To evaluate our model we conducted an experiment in which users performed a multiscale comparison task using both zooming and multiple-window interfaces. The results confirm the general predictions of our model.
A demonstration of the Polaris poker system
Authors: Michael Bowling, Nicholas Abou Risk, Nolan Bard, Darse Billings, Neil Burch, Joshua Davidson, John Hawkin, Robert Holte, Michael Johanson, Morgan Kan, Bryce Paradis, Jonathan Schaeffer, David Schnizlein, Duane Szafron, Kevin Waugh, Martin Zinkevich
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2 (2009)

Poker games provide a useful testbed for modern Artificial Intelligence techniques. Unlike many classical game domains such as chess and checkers, poker includes elements of imperfect information, stochastic events, and one or more adversarial agents to interact with. Furthermore, in poker it is possible to win or lose by varying degrees. Therefore, it can be advantageous to adapt ones' strategy to exploit a weak opponent. A poker agent must address these challenges, acting in uncertain environments and exploiting other agents, in order to be highly successful. Arguably, poker games more closely resemble many real world problems than games with perfect information. In this brief paper, we outline Polaris, a Texas Hold'em poker program. Polaris recently defeated top human professionals at the Man vs. Machine Poker Championship and it is currently the reigning AAAI Computer Poker Competition winner in the limit equilibrium and no-limit events.
A polyrepresentational approach to interactive query expansion
Authors: Abdigani Diriye, Ann Blandford, Anastasios Tombros
Venue: Proceedings of the 9th ACM/IEEE-CS joint conference on Digital libraries (2009)

Interactive Query Expansion (IQE) presents suggested terms to the user during their search to enable better Information Retrieval (IR). However, IQE terms are poorly used, and tend to lack information meaningful to the user. The lack of cognitive and functional support during query refinement is a well documented problem, and despite the work carried out, it is still an under researched area. This stagnation in progress has been partly due to the long held belief that users are able to make good IQE term selections, and that the de facto way IQE terms are presented is effective. In this paper, we introduce a novel method to improve the presentation of IQE terms by providing supplementary information alongside them. We describe a user study that compared our novel polyrepresentational approach to IQE against a conventional IQE system and a baseline system. Our findings have shown that a polyrepresentational approach to IQE can address the ambiguity and uncertainty surrounding IQE, and improve the perceived usefulness of the terms.
Who the Heck Is the Father of Bob?
Authors: Marko Luther, Thorsten Liebig, Sebastian Böhm, Olaf Noppens
Venue: Proceedings of the 6th European Semantic Web Conference on The Semantic Web: Research and Applications (2009)

Finding the optimal selection of an OWL reasoner and service interface for a specific ontology-based application is challenging. Over time it has become more and more difficult to match application requirements with service offerings from available reasoning engines, in particular with recent optimizations for certain reasoning services and new reasoning algorithms for different fragments of OWL. This work is motivated by real-world experiences and reports about interesting findings in the course of developing an ontology-based application. Benchmarking outcomes of several reasoning engines are discussed --- especially with respect to accompanying sound and completeness tests. We compare the performance of various service and communication protocols in different computing environments. Hereby, it becomes apparent that these largely underrated components may have an enormous impact on the overall performance.
Destabilization of adversarial organizations with strategic interventions
Authors: Kathleen M. Carley
Venue:  (2008)

Destabilization of adversarial organizations is crucial to combating terrorism. The adversarial organizations are complex adaptive systems, which include different types of entities and links to perform complex tasks and evolve over-time to adapt to changing situations. Both the complexity and the adaptivity of the adversary make it difficult for friendly forces to destabilize the adversary and to damage the performance of the adversary's organization. By taking a dynamic network analytic approach and focusing on how to identify, reason about, and break (1) the adversary's decision making structure, (2) the likelihood that the adversary can engage in key tasks; and (3) the adversary's over-time social and geospatial behavior, we can begin to make headway in reasoning about this complexity and adaptivity. I develop four different, interoperable approaches supporting this assessment and estimation on adversarial organizations. These four approaches analyze different aspects of an organization, i.e. the core decision making structure, the high level assessment of task completion likelihood and the micro level simulation of the behavior of adversaries. By unifying these approaches, we can grasp a complete picture of the target as well as the destabilization strategies against it. To ground and demonstrate this research, I use, primarily, three adversarial organizations, the terrorist networks responsible for 1998 US embassy bombing in Tanzania and Kenya; 1998 US embassy bombing in Kenya; and a global terrorist network. My research makes contribution at theoretical, technical and empirical levels. First, I provide a theory of how to create a joint picture from different organizational and computational theories. Second, I develop and test an interoperable analysis framework supported by the suggested joint theory. Third, I empirically analyze three adversarial organizations to demonstrate the usage of this framework and the newly enabled analysis results. This unifying theory and framework for adversarial destabilization, a partially automated intelligence analysis capability, (1) provide intelligence analysis results that can meet the operation tempo in the real world, (2) bridge dynamic network analysis and various inference theories, and (3) provide a better tool that human analysts may use to reduce their time and cost of destabilization analysis.
Towards traceability from project management to system models
Authors: Jonas Helming, Maximilian Koegel, Helmut Naughton
Venue: Proceedings of the 2009 ICSE Workshop on Traceability in Emerging Forms of Software Engineering (2009)

Traceability is commonly known as the ability to describe and follow links between artifacts, e.g. between requirements and their corresponding part of the system design. These links are typically inside of the system specification. Very few approaches consider traceability between the system specification and project management artifacts. By introducing links between these two models, a task can be traced to the system model elements it is related to. This paper proposes a unified model, which explicitly combines project management models and system specification models to enable traceability. We introduce and discuss the following key concepts, which are currently evaluated in a case study: (1) Ability to navigate between tasks and the according part of the specification, (2) Project management status aggregation by system specification artifacts, (3) Use of entities from the system model for project planning, (4) Unified model validation.
A model of topology cache in reactive routing protocols for MANETs
Authors: Andres Medina, Stephan Bohacek
Venue: Proceedings of the 4th Annual International Conference on Wireless Internet (2008)

In a reactive routing protocol such as DSR, when a route search message is flooded, a large number of nodes learn the path to the originator of the search. Moreover, each of these nodes learns paths to all upstream nodes along the route to the originator. Thus, during a route search, a large amount of topology information is distributed and stored in cache. This information is then used to reduce the number of hops future route search messages must travel. In this paper a model of the impact of topology cache is developed. The model allows the impact of cache to be estimated for a wide range of node speeds, node densities, network sizes, and values of cache timeout. When compared to simulation, the model predicts the number of hops that the route search message spreads within 10%. This model allows a wide range of analysis to be performed. For example, the paper includes an investigation of optimal cache timeout and an investigation of the impact of cache in highly mobile environments.
Position Tracking for Non-linear Teleoperators with Variable Time Delay
Authors: Emmanuel Nuño, Luis Basañez, Romeo Ortega, Mark W. Spong
Venue: International Journal of Robotics Research (2009)

In this paper the problem of position tracking in the presence of variable time delay is studied. It is proved that simple P-like and PD-like controllers can stabilize the teleoperator under variable time delays and, moreover, they provide position tracking. Then, a controller based on the scattering transformation that also provides position tracking is proposed. In this paper we present the conditions under which the velocities and position error of the non-linear teleoperator, for the three controllers, are bounded, and if the human does not move the local manipulator and the remote manipulator does not interact with the environment, then it is proved that velocities and position error converge to zero. Simulations and real experiments, using the Internet from Urbana-Champaign (USA) to Barcelona (Spain), validate the proposed schemes.
Is Over Practice Necessary? --Improving Learning Efficiency with the Cognitive Tutor through Educational Data Mining
Authors: Hao Cen, Kenneth R. Koedinger, Brian Junker
Venue: Proceeding of the 2007 conference on Artificial Intelligence in Education: Building Technology Rich Learning Contexts That Work (2007)

This study examined the effectiveness of an educational data mining method --Learning Factors Analysis (LFA) --on improving the learning efficiency in the Cognitive Tutor curriculum. LFA uses a statistical model to predict how students perform in each practice of a knowledge component (KC), and identifies over-practiced or under-practiced KCs. By using the LFA findings on the Cognitive Tutor geometry curriculum, we optimized the curriculum with the goal of improving student learning efficiency. With a control group design, we analyzed the learning performance and the learning time of high school students participating in the Optimized Cognitive Tutor geometry curriculum. Results were compared to students participating in the traditional Cognitive Tutor geometry curriculum. Analyses indicated that students in the optimized condition saved a significant amount of time in the optimized curriculum units, compared with the time spent by the control group. There was no significant difference in the learning performance of the two groups in either an immediate post test or a two-week-later retention test. Findings support the use of this data mining technique to improve learning efficiency with other computer-tutor-based curricula.
Cognitive and Motivational Effects of Animated Pedagogical Agent for Learning English as a Second Language
Authors: Sunhee Choi, Hyokyeong Lee
Venue: Proceeding of the 2005 conference on Artificial Intelligence in Education: Supporting Learning through Intelligent and Socially Informed Technology (2005)

This paper discusses the results of a pilot study that explores the cognitive and motivational effects of an animated pedagogical agent as well as an alternative delivery system (a simple flashing arrow with audio) in a multimedia environment in which college level ESL students learn English relative clauses. The study also examines the cognitive efficiency of these two media systems used to deliver the same instructional method for teaching English grammar.
Learning operational requirements from goal models
Authors: Dalal Alrajeh, Jeff Kramer, Alessandra Russo, Sebastin Uchitel
Venue: Proceedings of the 2009 IEEE 31st International Conference on Software Engineering (2009)

Goal-oriented methods have increasingly been recognised as an effective means for eliciting, elaborating, analysing and specifying software requirements. A key activity in these approaches is the elaboration of a correct and complete set of opertional requirements, in the form of pre- and trigger-conditions, that guarantee the system goals. Few existing approaches provide support for this crucial task and mainly rely on significant effort and expertise of the engineer. In this paper we propose a tool-based framework that combines model checking, inductive learning and scenarios for elaborating operational requirements from goal models. This is an iterative process that requires the engineer to identify positive and negative scenarios from counterexamples to the goals, generated using model checking, and to select operational requirements from suggestions computed by inductive learning.
Improved Object Tracking Algorithm Based on New HSV Color Probability Model
Authors: Gang Tian, Ruimin Hu, Zhongyuan Wang, Youming Fu
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part II (2009)

In this paper, an improved Cam-Shift algorithm is proposed. Traditional Cam-Shift algorithm only used H component in the HSV color space to build target color histogram, H color histogram is a relatively weak description of the characteristics of the target, so the algorithm is ineffective when the color distribution of the background and object is similar. Different with traditional algorithm, we building a new HSV combined color histogram model based on the character of human visual system, which is more sensitive to colors. The experiment results prove the new method can make a more accurate tracking result even in complex background.
Reasoning about edits to feature models
Authors: Thomas Thum, Don Batory, Christian Kastner
Venue: Proceedings of the 2009 IEEE 31st International Conference on Software Engineering (2009)

Features express the variabilities and commonalities among programs in a software product line (SPL). A feature model defines the valid combinations of features, where each combination corresponds to a program in an SPL. SPLs and their feature models evolve over time. We classify the evolution of a feature model via modifications as refactorings, specializations, generalizations, or arbitrary edits. We present an algorithm to reason about feature model edits to help designers determine how the program membership of an SPL has changed. Our algorithm takes two feature models as input (before and after edit versions), where the set of features in both models are not necessarily the same, and it automatically computes the change classification. Our algorithm is able to give examples of added or deleted products and efficiently classifies edits to even large models that have thousands of features.
Characterization of ZrO2 thin films deposited by MOCVD for high-density 3D capacitors
Authors: Magali Brunet, Emmanuel Scheid, Karolina Galicka-Fau, Michel Andrieux, Corinne Legros, Isabelle Gallet, Michaële Herbst, Sylvie Schamm
Venue: Microelectronic Engineering (2009)

This work deals with high-density integrated capacitors for output filters in future micro DC-DC converters. To reach high capacitance density, 3D structures were created in silicon with DRIE followed by MOCVD of ZrO"2 (100nm thick). The step coverage revealed two deposition regimes: a surface reaction controlled regime for cavities aspect ratio lower than 2 and a diffusion-controlled regime for higher aspect ratios. The ZrO"2 films present mostly a cubic/tetragonal structure. The permittivity extracted from the measurement is 26.4. These results are discussed with static dielectric responses calculated in literature.
Kohonen self-organizing maps and mass balance method for the supervision of a lowland river area
Authors: Frédérik Thiery, Esther Llorens, Stéphane Grieu, Monique Polit
Venue: Proceeding of the 2006 conference on Artificial Intelligence Research and Development (2006)

The Têt, main river of the Pyrénées-Orientales department (south of France) has a significant impact on the life of the department. The management of its water quality must be largely improved and better monitored. In this sense, the present work takes part in a global development and evaluation of reliable and robust tools, with the aim of allowing the control and supervision of the Têt River's lowland area. A simplified model, based on mass balances, has been developed to estimate nutrient levels in the stream and to describe the river water quality. Due to, the application of mathematical models for river water quality as support tools is often limited by the availability of reliable data, Kohonen self-organizing maps were used to solve it and to avoid the data missing. This kind of neural networks proved to be very useful to predict missing components and to complete the available database, describing the chemical state of the river and the WWTPs operation.
A Case of Blending Learning in Computer Teaching --The Model and the Application
Authors: Cuiling Li, Hong Wang, Huiyu Zhang
Venue: Proceeding of the 2006 conference on Learning by Effective Utilization of Technologies: Facilitating Intercultural Understanding (2006)

In this paper, firstly we introduce four key elements of application of blending learning in teaching, and then we talk about the application of blending learning in the field of computer teaching based on the practical case of curriculum of 'Fundamentals of Computer for University'.