ppxscal/embedding_network huggingface dataset:
Automatic learning and generation of social behavior from collective human gameplay
Authors: Jeff Orkin, Deb Roy
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 1 (2009)

Current approaches to authoring behavior and dialogue for agents that interact with humans in virtual environments are labor intensive, yet often yield less robust results than desired in the face of the incredible variance possible in human input. The growing number of people playing multiplayer games online provides a potentially better alternative to hand-authored content -- capturing behavior and dialogue from human-human interactions, and automating agents with this data. This paper documents promising results from the first iteration of a Collective Artificial Intelligence system that generates behavior and dialogue in real-time from data captured from over 11,000 players of The Restaurant Game. We first describe the game, the collective memory system, and the proposal-critique driven agent architecture, and then demonstrate quantitatively that our system preserves the texture, or meaningful local coherence, of human social interaction.
AQuSyNA-matlab application for automatic quantification of sympathetic nerve activity
Authors: Mili Turic, Mirjana Bonkovic, Suzana Cecic
Venue: Proceedings of the 10th WSEAS international conference on Automation & information (2009)

The main goal of this paper is to present the way we implement the method for automated quantification of sympathetic nerve activity. The implemented method belongs to the techniques based on the objective detection criteria and has user friendly application interface through which it is possible to eliminate artifacts and preserve a beat-by-beat SNA signal for a variety of subsequent analyses.
Taming Dynamically Adaptive Systems using models and aspects
Authors: Brice Morin, Olivier Barais, Gregory Nain, Jean-Marc Jezequel
Venue: Proceedings of the 2009 IEEE 31st International Conference on Software Engineering (2009)

Since software systems need to be continuously available under varying conditions, their ability to evolve at runtime is increasingly seen as one key issue. Modern programming frameworks already provide support for dynamic adaptations. However the high-variability of features in Dynamic Adaptive Systems (DAS) introduces an explosion of possible runtime system configurations (often called modes) and mode transitions. Designing these configurations and their transitions is tedious and error-prone, making the system feature evolution difficult. While Aspect-Oriented Modeling (AOM) was introduced to improve the modularity of software, this paper presents how an AOM approach can be used to tame the combinatorial explosion of DAS modes. Using AOM techniques, we derive a wide range of modes by weaving aspects into an explicit model reflecting the runtime system. We use these generated modes to automatically adapt the system. We validate our approach on an adaptive middleware for home-automation currently deployed in Rennes metropolis.
Presumptions and Burdens of Proof
Authors: Henry Prakken, Giovanni Sartor
Venue: Proceeding of the 2006 conference on Legal Knowledge and Information Systems: JURIX 2006: The Nineteenth Annual Conference (2006)

This paper studies the logical modelling of presumptions and their effects on the burden of proof. Presumptions are modelled as default rules and their effect on the burden of proof is defined in terms of a distinction between the burden of production, the burden of persuasion and the tactical burden of proof. These notions are logically characterised in such a way that presumptions enable a party to fulfil a burden of production or persuasion while shifting a tactical burden to the other party. Finally, it is shown how debates about what can be presumed can be modelled as debates about the backings of default rules.
Challenges for Next Generation Network Operations and Service Management: a Report on APNOMS 2008
Authors: James Won-Ki Hong, Luoming Meng, Young-Tak Kim, Hiroshi Uno, Shingo Ata, Yan Ma, Deokjai Choi
Venue: Journal of Network and Systems Management (2009)

This article presents a report on APNOMS 2008, which was held October 22---24, 2008 in Beijing, China. The theme of APNOMS 2008 was "Challenges for Next Generation Network Operations and Service Management."
Conversational Interactions among Rational Agents
Authors: Philippe Lemoisson, Stefano A. Cerri, Jean Sallantin
Venue: Proceeding of the 2005 conference on Towards the Learning Grid: Advances in Human Learning Services (2005)

The new paradigm of “knowledge construction using experiential based and collaborative learning approaches” is an outstanding opportunity for interdisciplinary research. This document is an attempt to introduce and exemplify as much as possible using the lexicon of “social sciences”, considerations and tools belonging to “artificial intelligence”. In the paper we first draw a conceptual framework for rational agents in conversational interaction; then we use this framework for describing the processes of co-building ontologies, co-building theories, social interactive learning … as examples of constructive interactions; finally we give a brief description of a conversational protocol aimed at putting a stone in the middle of the gap between human conversation and calculus.
A diffusion approximation for batch queues of type GX/G(b,b)/1
Authors: Horst Zisgen
Venue: Performance Evaluation (2009)

Queues with bulk arrivals and batch service arise in a variety of application areas, in particular in the performance analysis of manufacturing lines, like semiconductor fabrications. In the course of this paper, a diffusion approximation for queueing systems with bulk arrivals and batch service for general and independent interarrival time distributions, as well as general service time distributions, is presented. The approximation uses a modified absorbing barrier and instantaneous return approach. The accuracy of the gained approximation is shown by a subsequent comparison with the corresponding discrete event simulation results.
Context-Aware Data Management- An Object-Oriented Version Model
Authors: Michael Grossniklaus
Venue:  (2007)

Context-awareness is a requirement of many modern applications. While several solutions exist to gather, represent and process context, very few provide management of context-aware data. In this book, a two-dimensional version model is presented, that allows managing context-dependent variants, while, at the same time, keeping track of the revision history. Queries are processed based on a matching algorithm that uses the current context of the system to select the best object. As an application of this extended database, a content management system has been designed and implemented. This Extensible Content Management System (XCM) provides a flexible platform for web engineering, built on the separation of content, structure, view and presentation. Metadata about these concepts is managed within the extended database and therefore all aspects of a web system become context-aware. Using XCM, a mobile tourist information system (EdFest) was developed. EdFest offers multi-channel interaction through standard web channels and a novel paper-based channel. This book is targeted at developers and researchers in mobile, ubiquitous and pervasive computing as well as in web engineering.
WWW sits the SAT: Measuring Relational Similarity on the Web
Authors: Danushka Bollegala, Yutaka Matsuo, Mitsuru Ishizuka
Venue: Proceeding of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence (2008)

Measuring relational similarity between words is important in numerous natural language processing tasks such as solving analogy questions and classifying noun-modifier relations. We propose a method to measure the similarity between semantic relations that hold between two pairs of words using a web search engine. First, each pair of words is represented by a vector of automatically extracted lexical patterns. Then a Support Vector Machine is trained to recognize word pairs with similar semantic relations. We evaluate the proposed method on SAT multiple-choice word-analogy questions. The proposed method achieves a score of 40% which is comparable with relational similarity measures which use manually created resources such as WordNet. The proposed method significantly reduces the time taken by previously proposed computationally intensive methods, such as latent relational analysis, to process 374 analogy questions from 8 days to less than 6 hours.
The Art of Programming or Programs as Art
Authors: Ernest Edmonds
Venue: Proceeding of the 2007 conference on New Trends in Software Methodologies, Tools and Techniques: Proceedings of the sixth SoMeT_07 (2007)

The paper reviews developments in the implications of software programming in art practice whilst pointing to a recognition of the art in programming. The concerns in software-based art are significantly more conceptual than was often the case before. Following the Russian constructivist artists, the software artist is more concerned with the plan for making the work than for conventional rules of composition. The paper reviews a history of the author's use of various software representations in his art practice and proposes that art is all the richer for embracing software but, in so doing, the challenge to the artist is to be at least as deeply involved in software as in any other aspect of their practice.
Application of expert systems in medicine
Authors: Francklin Rivas Echeverría, Carlos Rivas Echeverría
Venue: Proceeding of the 2006 conference on Artificial Intelligence Research and Development (2006)

In this talk, we will present some development of expert system for decision-making in diagnosis and treatment in medicine. These systems guide the user to collect easily the patient information, based on those information points that can lead to a possible diagnose and to the adapted treatment of the diseases. They guide the user during the medical examination (physical) that will be done on the patient showing the definitions, images, sounds and/or videos of the signs associated to their disease and verify that the doctor does not forget to examine none of the criteria diagnoses even though is the first time that he sees or knows this sign. Once the patient data collected, the diagnose is based on the stored medical knowledge. The data on symptoms or signs, special data of laboratory or tests or radiological images are process by the system using defined rules to obtain the possible diagnoses. Additional data such as the presence or absence of certain signs and symptoms help to make a final diagnose. The rules of these Expert systems include the diagnose criteria from world-wide Associations, as well as algorithms designed by members of the Laboratory of Intelligent Systems of the University of The Andes. The qualities of this system are: 1. It can diagnose of one or more diseases and suggests the appropriate therapy. 2. It diagnoses the absolute absence of anyone of these diseases. 3. It can find some symptoms or signs due to any exogenous cause (a differential diagnose). 4. It notifies to the doctor that the patient does not fill the minimum criteria for some of the diseases and in this case, suggests a new evaluation. 5. It suggests send the patient to a specialist. The reasoning for establishing diagnoses or hypotheses of diagnoses is given as well as the plans for other examinations and for patient treatment. Also it is indicated when there are inexplicable signs, symptoms or laboratory data. They include the realization of a set of questions individualized for each subject and the selection of data that is going to be acquired answering the questions.
Evaluating Anthropomorphic Product Recommendation Agents: A Social Relationship Perspective to Designing Information Systems
Authors: Lingyun Qiu, Izak Benbasat
Venue: Journal of Management Information Systems (2009)

In online shopping environments, the product-advising function originally performed by salespeople is being increasingly taken over by software-based product recommendation agents (PRAs). However, the literature has mostly focused on the functionality design and utilitarian value of such decision support systems, mostly ignoring the potential social influence they could exert on their users. The objective of this study is to apply a social relationship perspective to the design of interfaces for PRAs. We investigate the effects of applying anthropomorphic interfaces-namely, humanoid embodiment and voice output-on users' perceived social relationship with a technological and software-based artifact designed for electronic commerce contexts. The findings from a laboratory experiment indicate that using humanoid embodiment and human voice-based communication significantly influences users' perceptions of social presence, which in turn enhances users' trusting beliefs, perceptions of enjoyment, and ultimately, their intentions to use the agent as a decision aid. These results extend the applicability of theories concerning traditional shopper-salesperson relationships to customers' interactions with technological artifacts residing on Web sites-that is, the recommendation agent software-and provide practitioners with guidelines on how to design Internet stores with the goal of building social relationships with online shoppers and enhancing their overall shopping experiences.
Potential Field Based Camera Collisions Detection within Translating 3D Objects
Authors: Adam Wojciechowski
Venue: Proceedings of the International Conference on Computer Vision and Graphics: Revised Papers (2008)

Existing collision detection methods usually need long precalculation stage or difficult, time-consuming real-time computation. Moreover its effectiveness considerably decreases while the complexity of the scene or objects increases. Especially dynamic scenes with moving objects invoke necessity of each frame collisions recalculation due to changeable objects position. So far seemingly promising solutions supported by potential fields do not introduce satisfactory functionality as they are mainly devoted to static scenes with one predefined aim. This paper introduces method providing a new potential field construction which lets the camera reach both static and translating objects without constraints and protects user from getting into their structure while approaching volatile goals. Additionally proposed method comprises easy to bring through pre- calculation stage and becomes a scene-complexity independent solution.
Hierarchical difference scatterplots interactive visual analysis of data cubes
Authors: Harald Piringer, Matthias Buchetics, Helwig Hauser, Eduard Gröller
Venue: Proceedings of the ACM SIGKDD Workshop on Visual Analytics and Knowledge Discovery: Integrating Automated Analysis with Interactive Exploration (2009)

Data cubes as employed by On-Line Analytical Processing (OLAP) play a key role in many application domains. The analysis typically involves to compare categories of different hierarchy levels with respect to size and pivoted values. Most existing visualization methods for pivoted values, however, are limited to single hierarchy levels. The main contribution of this paper is an approach called Hierarchical Difference Scatterplot (HDS). A HDS allows for relating multiple hierarchy levels and explicitly visualizes differences between them in the context of the absolute position of pivoted values. We discuss concepts of tightly coupling HDS to other types of tree visualizations and propose the integration in a setup of multiple views, which are linked by interactive queries on the data. We evaluate our approaches by analyzing social survey data in collaboration with a domain expert.
Mapping Sustainability: Knowledge e-Networking and the Value Chain, 1st edition
Authors: Nazli Choucri, Nazli Choucri, Dinsha Mistree, Farnaz Haghseta, Toufic Mezher, Wallace R. Baker, Carlos I. Ortiz
Venue:  (2007)

This book focuses on three interdependent challenges related to managing transitions toward sustainable development, namely (a) mapping sustainability for global knowledge e-networking, (b) extending the value chain of knowledge and e-networking, and (c) engaging in explorations of new methods and venues for further developing knowledge and e-networking. While each of these challenges constitutes fundamentally different types of endeavors, they are highly interconnected. Jointly, they contribute to our expansion of knowledge and its applications in support of transitions toward sustainable development.
An Improved Parameterized Algorithm for&#x00a0;the&#x00a0;Minimum Node Multiway Cut Problem
Authors: Jianer Chen, Yang Liu, Songjian Lu
Venue: Algorithmica (2009)

The parameterized node multiway cut problem is for a given graph to find a separator of size bounded by k whose removal separates a collection of terminal sets in the graph. In this paper, we develop an O(k4k n 3) time algorithm for this problem, significantly improving the previous algorithm of time $O(4^{k^{3}}n^{5})$for the problem. Our result gives the first polynomial time algorithm for the minimum node multiway cut problem when the separator size is bounded by O(log&#x2009;n).
Hierarchical result views for keyword queries over relational databases
Authors: Shiyuan Wang, Junichi Tatemura, Arsany Sawires, Oliver Po, Divyakant Agrawal, Amr El Abbadi
Venue: Proceedings of the First International Workshop on Keyword Search on Structured Data (2009)

Enabling keyword queries over relational databases (KQDB) benefits a large population of users who have difficulty in understanding the database schema or using SQLs. However, since there are different interpretations for a query, the results of KQDB that mix different possible answers still make it hard for users to consume and extract the information that is interesting to them. To help users with different preferences understand the query results and quickly locate the desired information, this paper proposes generating easy-to-navigate hierarchical result views for each interpretation to the query on the fly. We define the structures for organizing these hierarchical views, provide metrics for evaluating them in terms of user navigation efforts, and develop an efficient algorithm for generating the view structures. The effectiveness and efficiency of the proposed approaches are verified through an experimental study.
Database research in computer games
Authors: Alan Demers, Johannes Gehrke, Christoph Koch, Ben Sowell, Walker White
Venue: Proceedings of the 35th SIGMOD international conference on Management of data (2009)

This tutorial presents an overview of the data management issues faced by computer games today. While many games do not use databases directly, they still have to process large amounts of data, and could benefit from the application of database technology. Other games, such as massively multiplayer online games (MMOs), must communicate with commercial databases and have their own unique challenges. In this tutorial we will present the state-of-the-art of data management in games that we learned from our interaction with various game studios. We will show how the issues involved motivate current research, and illustrate several possibilities for future work. Our tutorial will start with a description of data-driven design, which is the source of many of the data management issues that games face. We will show some of the tools that game developers use to create and manage content. We will discuss how this type of design can affect performance, and the data structures and techniques that developers use to ensure that the game is responsive. We will discuss the problem of consistency in games, and how games ensure that players all share the same view of the world. Finally, we will examine some of the engineering issues that game developers have to deal with when interacting with traditional databases. This tutorial is intended to be self-contained, and provides the background necessary for understanding how databases and database technology are relevant to computer games. This tutorial is accessible to students and researchers who, while perhaps not hardcore gamers themselves, are interested in ways in which they can use their expertise to solve problems in computer games.
Feature shaping for linear SVM classifiers
Authors: George Forman, Martin Scholz, Shyamsundar Rajaram
Venue: Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining (2009)

Linear classifiers have been shown to be effective for many discrimination tasks. Irrespective of the learning algorithm itself, the final classifier has a weight to multiply by each feature. This suggests that ideally each input feature should be linearly correlated with the target variable (or anti-correlated), whereas raw features may be highly non-linear. In this paper, we attempt to re-shape each input feature so that it is appropriate to use with a linear weight and to scale the different features in proportion to their predictive value. We demonstrate that this pre-processing is beneficial for linear SVM classifiers on a large benchmark of text classification tasks as well as UCI datasets.
Group recognition through social norms
Authors: Daniel Villatoro, Jordi Sabater-Mir
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2 (2009)

This paper examines the decentralized recognition of groups within a multiagent normative society. In this work we explore different mechanisms that allow agents to recognize the others as members of a certain social group. Considering as the basic mechanism the one that makes agents interact with other agents without considering the previous interactions and with no communication, three new algorithms have been developed and tested to improve the efficiency of the basic one. These algorithms are: (1) the whitelisting, (2) the blacklisting, and (3) the labelling algorithm. Moreover, a reinterpretation of the definition of group is done in order to make it more dynamic and flexible with respect to the environment where agents are located. Analysis on simulation results confirms the effectiveness of this dynamic member evaluation function.
Exploring deep knowledge resources in biomedical name recognition
Authors: Zhou GuoDong, Su Jian
Venue: Proceedings of the International Joint Workshop on Natural Language Processing in Biomedicine and its Applications (2004)

In this paper, we present a named entity recognition system in the biomedical domain. In order to deal with the special phenomena in the biomedical domain, various evidential features are proposed and integrated through a Hidden Markov Model (HMM). In addition, a Support Vector Machine (SVM) plus sigmoid is proposed to resolve the data sparseness problem in our system. Besides the widely used lexical-level features, such as word formation pattern, morphological pattern, out-domain POS and semantic trigger, we also explore the name alias phenomenon, the cascaded entity name phenomenon, the use of both a closed dictionary from the training corpus and an open dictionary from the database term list SwissProt and the alias list LocusLink, the abbreviation resolution and indomain POS using the GENIA corpus.
NaXi pictographs information processing system
Authors: Guo Hai, Zhao Jing-ying
Venue: WSEAS TRANSACTIONS on SYSTEMS (2009)

This Paper describes a NaXi pictographs information processing system we developed for different applications. It sets a basis for computerization of NaXi pictographs. Basic NaXi pictographs information processing Font, IME (Input Method Editors) and corresponding application software have been realized. This sets an end to the history that the NaXi pictographs can't be handled with computers. It will greatly promote the computerization process of the minority languages.