ppxscal/embedding_network huggingface dataset:
The Roles of Active Perception in Intelligent Agent Systems
Authors: Raymond So, Liz Sonenberg
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)

This paper discusses the need to incorporate the notion of active perception in intelligent agent systems. There are two justifications for this proposition. First, we believe perception should receive more attention and some special treatment. Perception is the most direct and effective way to update an agent's beliefs about the status of its environment. In theory, an overwhelming portion of an agent's decisions about its next course of action, or next actions, in either the reactive or deliberative model, should be heavily influenced by what is happening in the environment --- this is one of the important characteristics that differentiates agents from the traditional software design paradigm. An agent's internal activities, such as deliberation and means-end analysis, to a large extent, are also driven by what have been sensed. The second justification is that active perception plays an imperative role in situation awareness. Active perception is an important capability that directs an agent's limited attention to the relevant aspects of the environment in an proactive manner.
Anticipatory perceptual simulation for human-robot joint practice: theory and application study
Authors: Guy Hoffman, Cynthia Breazeal
Venue: Proceedings of the 23rd national conference on Artificial intelligence - Volume 3 (2008)

With the aim of fluency and efficiency in human-robot teams, we have developed a cognitive architecture based on the neuro-psychological principles of anticipation and perceptual simulation through top-down biasing. An instantiation of this architecture was implemented on a nonanthropomorphic robotic lamp, performing in a human-robot collaborative task. In a human-subject study, in which the robot works on a joint task with untrained subjects, we find our approach to be significantly more efficient and fluent than in a comparable system without anticipatory perceptual simulation. We also show the robot and the human to be increasingly contributing at a similar rate. Through self-report, we find significant differences between the two conditions in the sense of team fluency, the team's improvement over time, and the robot's contribution to the efficiency and fluency. We also find difference in verbal attitudes towards the robot: most notably, subjects working with the anticipatory robot attribute more positive and more human qualities to the robot, but display increased self-blame and self-deprecation.
Exploiting subjectivity classification to improve information extraction
Authors: Ellen Riloff, Janyce Wiebe, William Phillips
Venue: Proceedings of the 20th national conference on Artificial intelligence - Volume 3 (2005)

Information extraction (IE) systems are prone to false hits for a variety of reasons and we observed that many of these false hi ts occur in sentences that contain subjective language (e.g., opinions, emotions, and sentiments). Motivated by these observations, we explore the idea of using subjectivity analysis to improve the precision of information extraction systems. In this paper, we describe an IE system that uses a subjective sentence classifier to filter its extractions. We experimented with several different strategies for using the subjectivity classifications, including an aggressive strategy that discards all extractions found in subjective sentences and more complex strategies that selectively discard extractions. We evaluated the performance of these different approaches on the MUC-4 terrorism data set. We found that indiscriminately filtering extractions from subjective sentences was overly aggressive, but more selective filtering strategies improved IE precision with minimal recall loss.
Confidence Measures for Error Correction in Interactive Transcription Handwritten Text
Authors: Lionel Tarazón, Daniel Pérez, Nicolás Serrano, Vicent Alabau, Oriol Ramos Terrades, Alberto Sanchis, Alfons Juan
Venue: Proceedings of the 15th International Conference on Image Analysis and Processing (2009)

An effective approach to transcribe old text documents is to follow an interactive-predictive paradigm in which both, the system is guided by the human supervisor, and the supervisor is assisted by the system to complete the transcription task as efficiently as possible. In this paper, we focus on a particular system prototype called GIDOC, which can be seen as a first attempt to provide user-friendly, integrated support for interactive-predictive page layout analysis, text line detection and handwritten text transcription. More specifically, we focus on the handwriting recognition part of GIDOC, for which we propose the use of confidence measures to guide the human supervisor in locating possible system errors and deciding how to proceed. Empirical results are reported on two datasets showing that a word error rate not larger than a 10% can be achieved by only checking the 32% of words that are recognised with less confidence.
Discovering Patterns in Flows: A Privacy Preserving Approach with the ACSM Prototype
Authors: Stéphanie Jacquemont, François Jacquenet, Marc Sebban
Venue: Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part II (2009)

In this demonstration, we aim to present the ACSM prototype that deals with the discovery of frequent patterns in the context of flow management problems. One important issue while working on such problems is to ensure the preservation of private data collected from the users. The approach presented here is based on the representation of flows in the form of probabilistic automata. Resorting to efficient algebraic techniques, the ACSM prototype is able to discover from those automata sequential patterns under constraints. Contrary to standard sequential pattern techniques that may be applied in such contexts, our prototype makes no use of individuals data.
HTTP Traffic Measurements on Access Networks, Analysis of Results and Simulation
Authors: Vladimir Deart, Vladimir Mankov, Alexander Pilugin
Venue: Proceedings of the 9th International Conference on Smart Spaces and Next Generation Wired/Wireless Networking and Second Conference on Smart Spaces (2009)

Many new factors influence on Internet Traffic nowadays including new features of HTTP/1.1, introduction of new browsers, extremely high penetration of P2P applications and changes in WEB content. A new Toolkit was used by authors to measure Traffic on access network of 1500 users in the center of Moscow. The collected data was handled for 2 levels: TCP connections level and HTTP Message level. Intervals between TCP connections and HTTP Request and Response Length were studied in details. Based on the collected statistics a new HTTP Traffic Model was built by using NS2 simulator and PackMIME package.
On-Site Evaluation of the Interactive COHIBIT Museum Exhibit
Authors: Patrick Gebhard, Susanne Karsten
Venue: Proceedings of the 9th International Conference on Intelligent Virtual Agents (2009)

This paper presents the results of a field study of the COHIBIT museum exhibit. Its purpose is to convey knowledge about car-technology and virtual characters in an entertaining way. Two life-sized virtual characters interact with the visitors and support them in constructing car models with specific tangible car modules. The evaluation should reveal what makes the exhibit successful in terms of an overall user impression and how users rate the employed virtual characters. The focus of the evaluation is to measure the user experience that manifests in aspects like attraction, rejection and entertainment. Based on an analysis of relevant systems and evaluation models, an on-site evaluation for the COHIBIT exhibit has been designed. The results show that the positive user experience of the exhibit is mainly based on the non-task-specific aspects like virtual characters, joy of use and entertainment.
Hierarchical differential game between manufacturer, retailer, and bank
Authors: E. V. Grigorieva, E. N. Khailov
Venue: Journal of Dynamical and Control Systems (2009)

In this work, a microeconomic model describing interactions between a manufacturer, retailer and bank is created and investigated. The manufacturer produces a single product, the retailer buys the good in order to resell it to the third party for a profit, and the bank lends the money. For the first time, a non-cooperative hierarchical game approach will be applied to a three-dimensional model with five bounded controls. The best optimal strategy for each player will be found analytically with the use of the Pontryagin Maximum Principle. A simulation software package is developed to demonstrate the performance of our proposed optimal algorithms.
MAID: A Multi-platform Accessible Interface Design Framework
Authors: Maria Korozi, Sterios Leonidis, George Margetis, Constantine Stephanidis
Venue: Proceedings of the 5th International Conference on Universal Access in Human-Computer Interaction. Part III: Applications and Services (2009)

Despite the outbreak in the development of new User Interface toolkits, the need for a combined toolkit that inherently supports adaptation to user needs and addresses accessibility issues still remains. MAID introduces a new approach to developing user interfaces that encapsulate new technology trends and also address individual users' needs. Additionally, MAID is accompanied by a library of adaptable widgets --- primitives and complex --- that allow designers to develop the actual user interfaces used by the MAID framework, eliminating thus the need for developers to be experts in user interface design and accessibility, in order to implement dynamic applications.
Security of Verifiably Encrypted Signatures and a Construction without Random Oracles
Authors: Markus Rückert, Dominique Schröder
Venue: Proceedings of the 3rd International Conference Palo Alto on Pairing-Based Cryptography (2009)

In a verifiably encrypted signature scheme, signers encrypt their signature under the public key of a trusted third party and prove that they did so correctly. The security properties, due to Boneh et al. (Eurocrypt 2003), are unforgeability and opacity.This paper proposes two novel fundamental requirements for verifiably encrypted signatures, called extractability and abuse-freeness, and analyzes its effects on the established security model. Extractability ensures that the trusted third party is always able to extract a valid signature from a valid verifiably encrypted signature and abuse-freeness guarantees that a malicious signer, who cooperates with the trusted party, is not able to forge a verifiably encrypted signature. We further show that both properties are not covered by the model of Boneh et al. The second main contribution of this paper is a verifiably encrypted signature scheme, provably secure without random oracles, that is more efficient and greatly improves the public key size of the only other construction in the standard model by Lu et al. (Eurocrypt 2006). Moreover, we present strengthened definitions for unforgeability and opacity in the spirit of strong unforgeability of digital signature schemes.
Repairing ontology mappings
Authors: C. Meilicke, H. Stuckenschmidt, Andrei Tamilin
Venue: Proceedings of the 22nd national conference on Artificial intelligence - Volume 2 (2007)

Automatically discovering semantic relations between ontologies is an important task with respect to overcoming semantic heterogeneity on the semantic web. Existing ontology matching systems, however, often produce erroneous mappings. In this paper, we address the problem of errors in mappings by proposing a completely automatic debugging method for ontology mappings. The method uses logical reasoning to discover and repair logical inconsistencies caused by erroneous mappings. We describe the debugging method and report experiments on mappings submitted to the ontology alignment evaluation challenge that show that the proposed method actually improves mappings created by different matching systems without any human intervention.
On the Readability of Monotone Boolean Formulae
Authors: Khaled Elbassioni, Kazuhisa Makino, Imran Rauf
Venue: Proceedings of the 15th Annual International Conference on Computing and Combinatorics (2009)

Golumbic et al. [Discrete Applied Mathematics 154(2006) 1465-1477] defined the readability of a monotone Boolean function f to be the minimum integer k such that there exists an ¿ ¿ ¿-formula equivalent to f in which each variable appears at most k times. They asked whether there exists a polynomial-time algorithm, which given a monotone Boolean function f, in CNF or DNF form, checks whether f is a read-k function, for a fixed k. In this paper, we partially answer this question already for k = 2 by showing that it is NP-hard to decide if a given monotone formula represents a read-twice function. It follows also from our reduction that it is NP-hard to approximate the readability of a given monotone Boolean function f:{0,1}n¿{0,1} within a factor of ${\mathcal O}(n)$. We also give tight sublinear upper bounds on the readability of a monotone Boolean function given in CNF (or DNF) form, parameterized by the number of terms in the CNF and the maximum size in each term, or more generally the maximum number of variables in the intersection of any constant number of terms. When the variables of the DNF can be ordered so that each term consists of a set of consecutive variables, we give much tighter polylogarithmic bounds on the readability.
A Case for a Packet Management in a Network Terminal
Authors: Yul Chu, Yan Bai, Amit Uppal, Jae Sok Son
Venue: Proceedings of the 2009 IEEE International Conference on Networking, Architecture, and Storage (2009)

In this paper, packet management of the protocol processor in a network terminal is investigated. Specifically, we have developed an algorithm that evenly distributes packet losses between different applications. Experimental studies have demonstrated that the algorithm works more efficiently than conventional dynamic algorithm when handling data streams with a speed high than than 10 Gb/s.
Research on Water Environmental Quality Assessment of Fu River with BP NN
Authors: Jinsheng Liu, Huanyin Zhou, Jinhui Liu, Jingying Chen
Venue: Proceedings of the 2009 International Conference on Environmental Science and Information Application Technology - Volume 01 (2009)

Fu River is an important river because of its rich freshwater resources while it has become some polluted because of industry development. Then how to correctly evaluate water quality becomes more and more important. In the field of water quality assessment, the evaluation factors and water quality grades have complicated non-linear relationships. BP (Back propagation) has been popularly used in every field which has the capability of dealing with non-linear systems. Artificial neural network model can easily solve the complex non-linear relationship by self-learning which can change weights of every layer without man involving. One BP neural network model on the water quality of Fu River assessment is built. Moreover, it can analyze the contaminated degree. BP NN (Network Neural) is improved as an effective water quality assessment method by one instance.
The Growing Semantic Web
Authors: Mark Greaves
Venue: Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part I (2009)

From its beginnings in 2004, the data available on the web in Semantic Web formats has typically been both eclectic and relatively small, and closely linked the interests of particular researchers. In the past year, however, the quantity and scope of data published on the public semantic web has exploded, and the size of the semantic web is now measured in the billions of assertions. It is a significant and growing resource for applications which depend on web-based resources for some or all of their knowledge. With this massive increase in quantity and scope come many opportunities, as well as the usual issues of scale on the web: inconsistency, mapping problems, incompleteness and data variability. This talk will cover the history and current state of the Semantic Web and the Linked Data Cloud, describe some of the uses to which web-based semantic data is currently put, and discuss prospects for the ECML/PKDD community to leverage this growing web of data.
HAPLO-ASP: Haplotype Inference Using Answer Set Programming
Authors: Esra Erdem, Ozan Erdem, Ferhan Türe
Venue: Proceedings of the 10th International Conference on Logic Programming and Nonmonotonic Reasoning (2009)

Identifying maternal and paternal inheritance is essential to be able to find the set of genes responsible for a particular disease. However, due to technological limitations, we have access to genotype data (genetic makeup of an individual), and determining haplotypes (genetic makeup of the parents) experimentally is a costly and time consuming procedure. With these biological motivations, we study haplotype inference--determining the haplotypes that form a given set of genotypes--using Answer Set Programming; we call our approach Haplo-ASP. This note summarizes the range of problems that can be handled by Haplo-ASP, and its applicability and effectiveness on real data in comparison with the other existing approaches.
Improving tractability of group decision making on environmental problems through the use of social intensities of preferences
Authors: Kamran Zendehdel, Michael Rademaker, Bernard De Baets, Guido Van Huylenbroeck
Venue: Environmental Modelling Software (2009)

Natural ecosystems play an essential role in the regulation and preservation of ecological processes and life support systems on earth. This observation increases social liability towards environmental protection. In the past people had mostly economic incentives to support environmental services, nowadays there are other motives such as ecological and social (non-economic) ones for supporting these services. However, the diversity of stakeholders' motives for environmental services is a source of conflict, which hinders natural resources managers to formulate an acceptable environmental policy. To alleviate this problem, we propose a tractable methodology to improve the acceptability of the group decision, based on the resolution of conflicts on environmental issues as one of the first steps in the methodology. The group decision aiding methodology we present is considered tractable as it reduces the number of concurrent inputs to be taken into account. It computes social intensities of preferences on environmental services to be processed by a conventional outranking method. In this way, stakeholders are able to verify that their opinion is taken into account, even if it is contrary to the majority voice. Natural resources managers who are responsible for environmental services will benefit from an increased insight into the prevalent opinion on each of the criteria through the supplied social intensities of preferences, enabling a more easily communicated justification of the final decision, and an augmented tractability of the decision making process.
IRST-BP: preposition disambiguation based on chain clarifying relationships contexts
Authors: Octavian Popescu, Sara Tonelli, Emanuele Pianta
Venue: Proceedings of the 4th International Workshop on Semantic Evaluations (2007)

We are going to present a technique of preposition disambiguation based on sense discriminative patterns, which are acquired using a variant of Angluin's algorithm. They represent the essential information extracted from a particular type of local contexts we call Chain Clarifying Relationship contexts. The data set and the results we present are from the Semeval task, WSD of Preposition (Litkowski 2007).
Transposition tables for constraint satisfaction
Authors: Christophe Lecoutre, Lakhdar Sais, Sébastien Tabary, Vincent Vidal
Venue: Proceedings of the 22nd national conference on Artificial intelligence - Volume 1 (2007)

In this paper, a state-based approach for the Constraint Satisfaction Problem (CSP) is proposed. The key novelty is an original use of state memorization during search to prevent the exploration of similar subnetworks. Classical techniques to avoid the resurgence of previously encountered conflicts involve recording conflict sets. This contrasts with our state-based approach which records subnetworks - a snapshot of some selected domains - already explored. This knowledge is later used to either prune inconsistent states or avoid recomputing the solutions of these subnetworks. Interestingly enough, the two approaches present some complementarity: different states can be pruned from the same partial instantiation or conflict set, whereas different partial instantiations can lead to the same state that needs to be explored only once. Also, our proposed approach is able to dynamically break some kinds of symmetries (e.g. neighborhood interchangeability). The obtained experimental results demonstrate the promising prospects of state-based search.
Robust Hybrid Tracking with Life-Size Avatar in Mixed Reality Environment
Authors: Qui Cong Tran, Shang Ping Lee, W. Russell Pensyl, Daniel Jernigan
Venue: Proceedings of the 3rd International Conference on Virtual and Mixed Reality: Held as Part of HCI International 2009 (2009)

We have developed a system which enables us to track participant-observers accurately in a large area for the purpose of immersing them in a mixed reality environment. This system is robust even under uncompromising lighting conditions. Accurate tracking of the observer's spatial and orientation point of view is achieved by using hybrid inertial sensors and computer vision techniques. We demonstrate our results by presenting life-size, animated human avatars sitting in real chairs, in a stable and low-jitter manner. The system installation allows the observers to freely walk around and navigate themselves in the environment even while still being able to see the avatars from various angles. The project installation provides and exciting way for cultural and historical narratives to be presented vividly in the real present world.
Hidden dynamic probabilistic models for labeling sequence data
Authors: Xiaofeng Yu, Wai Lam
Venue: Proceedings of the 23rd national conference on Artificial intelligence - Volume 2 (2008)

We propose a new discriminative framework, namely Hidden Dynamic Conditional Random Fields (HDCRFs), for building probabilistic models which can capture both internal and external class dynamics to label sequence data. We introduce a small number of hidden state variables to model the sub-structure of a observation sequence and learn dynamics between different class labels. An HDCRF offers several advantages over previous discriminative models and is attractive both, conceptually and computationally. We performed experiments on three well-established sequence labeling tasks in natural language, including part-of-speech tagging, noun phrase chunking, and named entity recognition. The results demonstrate the validity and competitiveness of our model. In addition, our model compares favorably with current state-of-the-art sequence labeling approach, Conditional Random Fields (CRFs), which can only model the external dynamics.