ppxscal/embedding_network huggingface dataset:
Emotional input for character-based interactive storytelling
Authors: Marc Cavazza, David Pizzi, Fred Charles, Thurid Vogt, Elisabeth André
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 1 (2009)

In most Interactive Storytelling systems, user interaction is based on natural language communication with virtual agents, either through isolated utterances or through dialogue. Natural language communication is also an essential element of interactive narratives in which the user is supposed to impersonate one of the story's characters. Whilst techniques for narrative generation and agent behaviour have made significant progress in recent years, natural language processing remains a bottleneck hampering the scalability of Interactive Storytelling systems. In this paper, we introduce a novel interaction technique based solely on emotional speech recognition. It allows the user to take part in dialogue with virtual actors without any constraints on style or expressivity, by mapping the recognised emotional categories to narrative situations and virtual characters feelings. Our Interactive Storytelling system uses an emotional planner to drive characters' behaviours. The main feature of this approach is that characters' feelings are part of the planning domain and are at the heart of narrative representations. The emotional speech recogniser analyses the speech signal to produce a variety of features which can be used to define ad-hoc categories on which to train the system. The content of our interactive narrative is an adaptation of one chapter of the XIXth century classic novel, Madame Bovary, which is well suited to a formalisation in terms of characters' feelings. At various stages of the narrative, the user can address the main character or respond to her, impersonating her lover. The emotional category extracted from the user utterance can be analysed in terms of the current narrative context, which includes characters' beliefs, feelings and expectations, to produce a specific influence on the target character, which will become visible through a change in its behaviour, achieving a high level of realism for the interaction. A limited number of emotional categories is sufficient to drive the narrative across multiple courses of actions, since it comprises over thirty narrative functions. We report results from a fully implemented prototype, both in terms of proof of concept and of usability through a preliminary user study.
Locally optimized MIC( 0) preconditioning of Rannacher--Turek FEM systems
Authors: I. Georgiev, J. Kraus, S. Margenov, J. Schicho
Venue: Applied Numerical Mathematics (2009)

In this paper Rannacher-Turek non-conforming rotated bilinear finite elements are applied for the numerical solution of second order elliptic boundary value problems. The preconditioned conjugate gradient method is used for the iterative solution of the arising linear algebraic system Au=f. A locally optimized construction for an M-matrix approximation B of the global stiffness matrix A is the first step of the proposed algorithm. Then, the preconditioner is obtained by modified incomplete Cholesky factorization of the auxiliary M-matrix B. A comparative analysis concerning three different approaches for construction of such matrices B is presented. The related spectral condition number estimates are derived. The most important contributions of the paper is the developed original robust preconditioning scheme for strongly anisotropic problems based on properly skewed meshes. A set of numerical tests is presented to illustrate the theoretical investigations.
Efficient Sensor Placement for Surveillance Problems
Authors: Pankaj K. Agarwal, Esther Ezra, Shashidhara K. Ganjugunte
Venue: Proceedings of the 5th IEEE International Conference on Distributed Computing in Sensor Systems (2009)

We study the problem of covering a two-dimensional spatial region P, cluttered with occluders, by sensors. A sensor placed at a location p covers a point x in P if x lies within sensing radius r from p and x is visible from p, i.e., the segment px does not intersect any occluder. The goal is to compute a placement of the minimum number of sensors that cover P. We propose a landmark-based approach for covering P. Suppose P has ¿ holes, and it can be covered by h sensors. Given a small parameter ¿> 0, let ¿: = ¿(h,¿) = (h/¿)(1 + ln (1 + ¿)). We prove that one can compute a set L of O(¿log¿ log(1/¿)) landmarks so that if a set S of sensors covers L, then S covers at least (1 ¿ ¿)-fraction of P. It is surprising that so few landmarks are needed, and that the number of landmarks depends only on h, and does not directly depend on the number of vertices in P. We then present efficient randomized algorithms, based on the greedy approach, that, with high probability, compute $O(\tilde{h}\log \lambda)$ sensor locations to cover L; here $\tilde{h} \le h$ is the number sensors needed to cover L. We propose various extensions of our approach, including: (i) a weight function over P is given and S should cover at least (1 ¿ ¿) of the weighted area of P, and (ii) each point of P is covered by at least t sensors, for a given parameter t ¿ 1.
A CSP approach for the network of product lifecycle constraints consistency in a collaborative design context
Authors: Pierre-Alain Yvars
Venue: Engineering Applications of Artificial Intelligence (2009)

In this paper, we are considering that the design process can be modelled in the form of a constraint satisfaction problem (CSP). CSP modelling or resolution has proved its efficiency within the framework of single-designer design. We propose to extend the functions of CSP to the context of multi-concept design of the same artefact. We define CoCSP as cooperative constraint satisfaction problem including the actors of the design problem. We are presenting the operating principles of an algorithm for the real-time management of design decisions, based on a model described in the form of a CoCSP for the integration of supply-chain constraints. This algorithm enables the number of design decisions rejected at a given moment in design to be kept to a minimum. The algorithm forms the core of a prototype for an unsupervised, generic constraint-based collaborative design system. Our aim is to produce a platform centred on the notion of constraints that will enable a product design problem to be modelled and solved by integrating supply-chain constraints as far upstream as possible.
Multi-agent Crisis Management in Transport Domain
Authors: Michał Konieczny, Jarosław Koźlak, Małgorzata Żabińska
Venue: Proceedings of the 9th International Conference on Computational Science (2009)

A multi-agent system that solves static and dynamic versions of transport problem (Pickup and Delivery Problem with Time Windows) in presence of crises is shown here. Scenarios to serve different kinds of crises (especially vehicle failures and traffic jams) by agents are described. The results summarising system functioning for solving classical PDPTW as well as influence of crises and applied algorithms of serving them upon quality of obtained solutions have been presented.
Fuzzy Document Clustering Based on Ant Colony Algorithm
Authors: Fei Wang, Dexian Zhang, Na Bao
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part II (2009)

This paper proposes a method of document clustering algorithm based on Ant Colony Algorithm (ACO) and Fuzzy C-means Clustering (FCM). First, the algorithm makes use of the great ability of Ant Colony Algorithm for finding local extremum. It's derived from a basic model interpreting ant colony organization of cemeteries. The ACO Algorithm for flexibility, self-organization and robustness has been applied in a variety of areas. Taking advantage of these traits, good initial clusters are obtained at first step in our algorithm. Then, we combine these with Fuzzy C-means clustering organically. We also find out the whole distributing optimization clustering process, and achieve clustering analysis based on improved function. Experimental results show the good performance of the hybrid document clustering algorithm.
Computer Society Connection
Authors: Bob Ward
Venue: Computer (2009)

Computer Society conferences address topics spanning all aspects of the computing profession and range in size from several dozen to several thousand participants.
Recent developments on graphs of bounded clique-width
Authors: Marcin Kamiński, Vadim V. Lozin, Martin Milanič
Venue: Discrete Applied Mathematics (2009)

Whether the clique-width of graphs in a certain class of graphs is bounded or not, is an important question from an algorithmic point of view, as many problems that are NP-hard in general admit polynomial-time solutions when restricted to graphs of bounded clique-width. Over the last few years, many classes of graphs have been shown to have bounded clique-width. For many others, this parameter has been proved to be unbounded. This paper provides a survey of recent results addressing this problem.
A numerical approach to design control invariant sets for constrained nonlinear discrete-time systems with guaranteed optimality
Authors: Jian Wan, Josep Vehi, Ningsu Luo
Venue: Journal of Global Optimization (2009)

A numerical approach to design control invariant sets for constrained nonlinear discrete-time systems with guaranteed optimality is proposed in this paper. The addressed approach is based on the fact that zonotopes are more flexible for representing sets than boxes in interval analysis. Then the solver of set inversion via interval analysis is extended to set inversion via zonotope geometry by introducing the novel idea of bisecting zonotopes. The main feature of the extended solver of set inversion is the bisection and the evolution of a zonotope rather than a box. Thus the shape of admissible domains for set inversion can be broadened from boxes to zonotopes and the wrapping effect can be reduced as well by using the zonotope evolution instead of the interval evolution. Combined with global optimization via interval analysis, the extended solver of set inversion via zonotope geometry is further applied to design control invariant sets for constrained nonlinear discrete-time systems in a numerical way. Finally, the numerical design of a control invariant set and its application to the terminal control of the dual-mode model predictive control are fulfilled on a benchmark Continuous-Stirred Tank Reactor example.
Authoring plug-in tutor agents by demonstration: Rapid, rapid tutor development
Authors: Vincent Aleven, Carolyn Rosé
Venue: Proceeding of the 2005 conference on Artificial Intelligence in Education: Supporting Learning through Intelligent and Socially Informed Technology (2005)

We combined two existing methods for rapid tutor development: “plug-in tutor agents” [6] and an authoring tool suite (CTAT) that supports the creation of tutors “by demonstration” [2]. The combined approach, which has not been tried before, is suited for adding tutoring capabilities to an existing problem-solving environment, for example an off-the-shelf simulator. Connecting the components (i.e., the simulator and CTAT) requires programming but once that is done, “Pseudo Tutors” are created “by demonstration. Following this approach, we created plug-in Pseudo Tutor agents for a thermodynamics simulator, CyclePad [1], which were tried out in a classroom experiment involving 92 college students. The experiment demonstrates that the Pseudo Tutor technology is viable in a complex domain and that Ritter and Koedinger's protocol for the tool-tutor communication is suited for use in an authoring environment.
Experience with Approximations in the Trust-Region Parallel Direct Search Algorithm
Authors: S. M. Shontz, V. E. Howle, P. D. Hough
Venue: Proceedings of the 9th International Conference on Computational Science: Part I (2009)

Recent years have seen growth in the number of algorithms designed to solve challenging simulation-based nonlinear optimization problems. One such algorithm is the Trust-Region Parallel Direct Search (TRPDS) method developed by Hough and Meza. In this paper, we take advantage of the theoretical properties of TRPDS to make use of approximation models in order to reduce the computational cost of simulation-based optimization. We describe the extension, which we call mTRPDS, and present the results of a case study for two earth penetrator design problems. In the case study, we conduct computational experiments with an array of approximations within the mTRPDS algorithm and compare the numerical results to the original TRPDS algorithm and a trust-region method implemented using the speculative gradient approach described by Byrd, Schnabel, and Shultz. The results suggest new ways to improve the algorithm.
Modelling the Human Values Scale in Recommender Systems: A first approach
Authors: Javier Guzmán, Gustavo González, Josep L. de la Rosa, José Castán
Venue: Proceeding of the 2005 conference on Artificial Intelligence Research and Development (2005)

The objective of this paper is two-fold. The first is to develop a methodology capable of extracting the Human Values Scale (HVS) from the user, with reference to his/her objective, subjective and emotional features, in order to improve the adaptation of user models to open environments, particularly in recommender systems. For this purpose a Coherence function is defined based on the user's emotional features profiled from his/her previous interactions with the system. This function is the mapping between the user behaviour and the relevance given by him/her in each life cycle of interactions. The second objective is to present preliminary results obtained from a case study using the objective, subjective and emotional attributes in the banking domain where the methodology was tested.
Information revelation and internet privacy concerns on social network sites: a case study of facebook
Authors: Alyson L. Young, Anabel Quan-Haase
Venue: Proceedings of the fourth international conference on Communities and technologies (2009)

Despite concerns raised about the disclosure of personal information on social network sites, research has demonstrated that users continue to disclose personal information. The present study employs surveys and interviews to examine the factors that influence university students to disclose personal information on Facebook. Moreover, we study the strategies students have developed to protect themselves against privacy threats. The results show that personal network size was positively associated with information revelation, no association was found between concern about unwanted audiences and information revelation and finally, students' Internet privacy concerns and information revelation were negatively associated. The privacy protection strategies employed most often were the exclusion of personal information, the use of private email messages, and altering the default privacy settings. Based on our findings, we propose a model of information revelation and draw conclusions for theories of identity expression.
Significant reduction of Positive Bias Temperature Instability in high-k/metal-gate nFETs by incorporation of rare earth metals
Authors: B. Kaczer, A. Veloso, M. Aoulaiche, G. Groeseneken
Venue: Microelectronic Engineering (2009)

A significant reduction of Positive Bias Temperature Instability (PBTI) in both planar and multiple-gate n-channel FET devices is reported after La and Dy incorporation into the HfSiO/TiN gate stack. Gate current reduction at low gate voltages is also seen in the La-passivated stack. Both observations are consistent with the theoretical prediction of rare earths passivating negatively charging oxygen vacancies in Hf oxide. Overcompensation of PBTI, i.e., the creation of positively charged defects is observed and is ascribed to an excessive amount of the rare earth element in the high-k layer.
Enrichment constrained time-dependent clustering analysis for finding meaningful temporal transcription modules
Authors: Jia Meng, Shou-Jiang Gao, Yufei Huang
Venue: Bioinformatics (2009)

Motivation: Clustering is a popular data exploration technique widely used in microarray data analysis. When dealing with time-series data, most conventional clustering algorithms, however, either use one-way clustering methods, which fail to consider the heterogeneity of temporary domain, or use two-way clustering methods that do not take into account the time dependency between samples, thus producing less informative results. Furthermore, enrichment analysis is often performed independent of and after clustering and such practice, though capable of revealing biological significant clusters, cannot guide the clustering to produce biologically significant result. Result:We present a new enrichment constrained framework (ECF) coupled with a time-dependent iterative signature algorithm (TDISA), which, by applying a sliding time window to incorporate the time dependency of samples and imposing an enrichment constraint to parameters of clustering, allows supervised identification of temporal transcription modules (TTMs) that are biologically meaningful. Rigorous mathematical definitions of TTM as well as the enrichment constraint framework are also provided that serve as objective functions for retrieving biologically significant modules. We applied the enrichment constrained time-dependent iterative signature algorithm (ECTDISA) to human gene expression time-series data of Kaposi's sarcoma-associated herpesvirus (KSHV) infection of human primary endothelial cells; the result not only confirms known biological facts, but also reveals new insight into the molecular mechanism of KSHV infection. Availability: Data and Matlab code are available at http://engineering.utsa.edu/~yfhuang/ECTDISA.html Contact: yufei.huang@utsa.edu Supplementary information:Supplementary data are available at Bioinformatics online.
Guideline for the definition of EMF metamodels using an Entity-Relationship approach
Authors: Iván García-Magariño, Rubén Fuentes-Fernández, Jorge J. Gómez-Sanz
Venue: Information and Software Technology (2009)

Metamodels are a formalism for defining the abstract syntax of modeling languages. However, designing a suitable metamodel from the features intended for the language is not a trivial task. This paper presents a guideline for defining such metamodels using an Entity-Relationship approach in the Eclipse Modeling Framework. This guideline proposes to begin by determining the structural features of the language, such as types of relationships and elements with attributes. Subsequently, it offers alternative representations for these features aimed at satisfying different requirements, such as changeability or optimized model processing. Two case studies illustrate the use of the guideline and its trade-offs.
An OCL extension for checking and transforming UML models
Authors: Thierry Millan, Laurent Sabatier, Thanh-Thanh Le Thi, Pierre Bazex, Christian Percebois
Venue: Proceedings of the 8th WSEAS International Conference on Software engineering, parallel and distributed systems (2009)

The increasing use of models in specification and design phases makes them first class citizens. Models which had, till now, been used to gain a better grasp of the software to be designed, have been attributed a productive role that has become central to development. This new status of models and meta-models poses the problem of how they are established and especially, how they are validated. So, each activity in a process can be supported by MDE (Model-Driven Engineering) components realizing transformations and verifications. These operations require redefining the OCL type system for taking into account multi-model handling and side-effects. Checking the transformation consists of ensuring that the source models and the targets respect a set of properties that can be verified through transformation contracts. The NEPTUNE platform was designed having this logic as a driving force - allowing the verification of models and of their transformation.
Dynamic Execution of Coordination Protocols in Open and Distributed Multi-Agent Systems
Authors: Wassim Bouaziz, Eric Andonoff
Venue: Proceedings of the Third KES International Symposium on Agent and Multi-Agent Systems: Technologies and Applications (2009)

Coordination protocols are widely recognized as an efficient mechanism to support agent interaction involved in modern Multi-Agent System (MAS) applications. This paper proposes a solution for dynamic execution of coordination protocols in such open and distributed MAS applications. More precisely, this paper shows how agents can dynamically take part in conversations, where the role they are intended to hold within a protocol is played without the need of prior knowledge.
Technical Section: Variational implicit surface meshing
Authors: Arnaud Gelas, Sébastien Valette, Rémy Prost, Wieslaw L. Nowinski
Venue: Computers and Graphics (2009)

In this paper, we propose a new algorithm to mesh implicit surfaces which produces meshes both with a good triangle aspect ratio as well as a good approximation quality. The number of vertices of the output mesh is defined by the end-user. For this goal, we perform a two-stage processing: an initialization step followed by an iterative optimization step. The initialization step consists in capturing the surface topology and allocating the vertex budget. The optimization algorithm is based on a variational vertices relaxation and triangulation update. In addition a gradation parameter can be defined to adapt the mesh sampling to the curvature of the implicit surface. We demonstrate the efficiency of the approach on synthetic models as well as real-world acquired data, and provide comparisons with previous approaches.
Indefinite Probabilities for General Intelligence
Authors: Matthew Iklé, Ben Goertzel, Izabela Goertzel
Venue: Proceeding of the 2007 conference on Advances in Artificial General Intelligence: Concepts, Architectures and Algorithms: Proceedings of the AGI Workshop 2006 (2007)

The creation of robust mechanisms for uncertain inference is central to the development of Artificial General Intelligence systems. While probability theory provides a principled foundation for uncertain inference, the mathematics of probability theory has not yet been developed to the point where it is possible to handle every aspect of the uncertain inference process in practical situations using rigorous probabilistic calculations. Due to the need to operate within realistic computational resources, probability theory presently requires augmentation with heuristics in order to be pragmatic for general intelligence (as well as for other purposes such as large-scale data analysis). The authors have been involved with the creation of a novel, general framework for pragmatic probabilistic inference in an AGI context, called Probabilistic Logic Networks (PLN). PLN integrates probability theory with a variety of heuristic inference mechanisms; it encompasses a rich set of first-order and higher-order inference rules, and it is highly flexible and adaptive, and easily configurable. This paper describes a single, critical aspect of the PLN framework, which has to with the quantification of uncertainty. In short, it addresses the question: What should an uncertain truth value be, so that a general intelligence may use it for pragmatic reasoning? We propose a new approach to quantifying uncertainty via a hybridization of Walley's theory of imprecise probabilities and Bayesian credible intervals. This “indefinite probability” approach provides a general method for calculating the “weight-of-evidence” underlying the conclusions of uncertain inferences. Moreover, both Walley's imprecise beta-binomial model and standard Bayesian inference can be viewed mathematically as special cases of the more general indefinite probability model. Via exemplifying the use of indefinite probabilities in a variety of PLN inference rules (including exact and heuristic ones), we argue that this mode of quantifying uncertainty may be adequate to serve as an ingredient of powerful artificial general intelligence.