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A Situated Game for Autistic Children Learning Activities of Daily Living

A Situated Game for Autistic Children Learning Activities of...

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IEEE International Workshop on Digital Game and Intelligent Toy Enhanced Learning (DIGITEL)

作者： Maiga Chang Rita Kuo Chun-Wei Lyu Jia-Sheng Heh School of Computing and Information Systems Athabasca University Canada Academic and Industrial Research Centre Knowledge Square Inc. Taiwan Department of Information and Computer Engineering Chung-Yuan Christian University Taiwan

Daily living skills are difficult for autistic children to learn because they have low motivation in learning new things. Some research has developed virtual environment to assist parents and teachers teaching autistic children daily living skills, educators still need to spend a lot of time in preparing personalized and more realistic tasks for children to practice. This research designs an activity generation mechanism by measuring activity's weight with fuzzy theory and rough set's help. Based on the activity generation mechanism and weight measurement, a Flash-based situated game is developed for providing autistic children personalized and non-repeated practices of activities of daily living. An evaluation plan of the pilot for verifying the effectiveness of the game and gathering the users' (include teachers, parents, and the autistic children) perceptions toward the game and the game-play is designed.

关键词： Games Videos Autism Automata Weight measurement Educational institutions

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Malay anaphor and antecedent candidate identification: A proposed solution

Malay anaphor and antecedent candidate identification: A pro...

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4th Asian Conference on Intelligent information and database systems, ACIIDS 2012

作者： Mohd Noor, Noorhuzaimi Karimah Noah, Shahrul Azman Ab Aziz, Mohd Juzaiddin Hamzah, Mohd Pouzi Faculty of Computer Systems and Software Engineering Universiti Malaysia Pahang Lebuhraya Tun Razak Pahang Kuantan 26300 Malaysia Knowledge Technology Research Group Faculty of Technology and Information Science Universiti Kebangsaan Malaysia Selangor Bangi 43600 Malaysia Department of Computer Science Faculty of Science Technology Universiti Malaysia Terengganu Terengganu Kuala Terengganu 21030 Malaysia

ISBN: (纸本)9783642284922

This paper discusses on Malay language anaphor and antecedent candidate determination using the knowledge-poor techniques. The process to determine the candidate for anaphor and antecedent is important because the usage of pronouns in a text is not always considered as an anaphor. Sometimes pronoun referred to something outside the context or does not refer to any situation in the text. Such a situation is also exhibited in the use of pronouns in Malay language. Therefore, certain rules must be issued to identify the antecedent and anaphor candidate. Pronoun usage in Malay language does indicate the gender of the person, but to distinguish the status of the person such as imperial family, honorable people and common people. Thus, generic rules that have been used by other languages cannot simply be adapted for Malay language. The proposed solution concerns with the distance of each candidate and location of the Subject-Verb-Object (SVO) used to determine the anaphor candidate. As such, syntactic information, semantic information and distance of anaphor-antecedent are seen important to determine the antecedent candidate. © 2012 Springer-Verlag.

关键词： Semantics

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The CULTURA project: CULTivating understanding and research through adaptivity

The CULTURA project: CULTivating understanding and research ...

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1st Workshop on Personalised Multilingual Hypertext Retrieval, PMHR 2011, Held in Conjunction with the ACM Hypertext 2011, HT2011

作者： Agosti, Maristella Lawless, Seamus Department of Information Engineering University of Padua Italy Knowledge and Data Engineering Group Trinity College Dublin Ireland

ISBN: (纸本)9781450308977

CULTURA will deliver personalisation and community-aware adaptivity for Digital Humanities communities through an innovative environment which is tailored to the investigation, comprehension and enrichment of digital humanities collections. CULTURA seeks to stimulate and support the communities of interest which form around such collections. © 2011 ACM.

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Meta-strategies in the Colored Trails Game

Meta-strategies in the Colored Trails Game

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23rd Benelux Conference on Artificial Intelligence, BNAIC 2011

作者： de Jong, Steven Hennes, Daniel Tuyls, Karl Gal, Ya'akov Department of Knowledge Engineering Maastricht University Netherlands Department of Information Systems Engineering Ben-Gurion University Israel

This paper1 presents a novel technique to reduce large-scale strategic interactions to bilateral normal-form games with a significantly smaller strategy space, while preserving many of the strategic characteristics of the original setting. We demonstrate our technique on the Colored Trails (CT) framework, which allows to model a large variety of multi-agent interactions. We define a set of representative heuristics describing players' actions, called meta-strategies, and show that a three-player CT game decomposes into pairwise social dilemma games. We also present a set of criteria for generating interesting CT game instances and show that these instances indeed decompose into social dilemmas.

关键词： Multi agent systems

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Metastrategies in the colored trails game

Metastrategies in the colored trails game

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10th International Conference on Autonomous Agents and Multiagent systems 2011, AAMAS 2011

作者： De Jong, Steven Hennes, Daniel Tuyls, Karl Gal, Ya'Akov Department of Knowledge Engineering Maastricht University Netherlands Department of Information Systems Engineering Ben-Gurion University of Negev Israel

ISBN: (纸本)9781618391018

This paper presents a novel method to describe and analyze strategic interactions in settings that include multiple actors, many possible actions and relationships among goals, tasks and resources. It shows how to reduce these large interactions to a set of bilateral normal-form games in which the strategy space is significantly smaller than the original setting, while still preserving many of its strategic characteristics. We demonstrate this technique on the Colored Trails (CT) framework, which encompasses a broad family of games defining multi-agent interactions and has been used in many past studies. We define a set of representative heuristics in a three- player CT setting. Choosing players' strategies from this set, the original CT setting is analytically decomposed into canonical bi-lateral social dilemmas, i.e.. Prisoners' Dilemma, Stag Hunt and Ultimatum games. We present a set of criteria for generating strategically interesting CT games and empirically show that they indeed decompose into bilateral social dilemmas if players play according to the heuristics. Our results have significance for multi-agent systems researchers in mapping large multi-player task settings to well-known bilateral normal-form games in a way that facilitates the analysis of the original setting. Copyright © 2011, International Foundation for Autonomous Agents and Multiagent systems.

关键词： Multi agent systems

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IROM: information retrieval-based ontology matching

IROM: Information retrieval-based ontology matching

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Lecture Notes in Computer Science

作者： Mousselly-Sergieh, Hatem Unland, Rainer Department of Distributed Information Systems University of Passau Passau Germany Data Management Systems and Knowledge Representation Group University of Duisburg-Essen Essen Germany

ISBN: (纸本)9783642230165

A crucial piece of semantic web development is the creation of viable ontology matching approaches to ensure interoperability in a wide range of applications such as information integration and semantic multimedia. In this paper, a new approach for ontology matching called IROM (information Retrieval-based Ontology Matching) is presented. This approach derives the different components of an information retrieval (IR) framework based on the information provided by the input ontologies and supported by ontology similarity measures. Subsequently, a retrieval algorithm is applied to determine the correspondences between the matched ontologies. IROM was tested with ontology pairs taken from two resources for reference ontologies, OAEI and FOAM. The evaluation shows that IROM is competitive with top-ranked matchers on the benchmark test at OAEI campaign of 2009. © 2011 Springer-Verlag.

关键词： Ontology

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Supporting vague query formulation by using visual filtering

Supporting vague query formulation by using visual filtering

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Symposium on Learning, knowledge, and Adaptivity 2011, LWA 2011

作者： Nitsche, Marcus Nurnberger, Andreas Institute for Technical and Business Information Systems Data and Knowledge Engineering Group Otto-von-Guericke-University Magdeburg D-39116 Magdeburg Germany

We propose a radial user interface which supports phrasing and interactive visual refinement of vague queries in order to search and explore large document sets. The core idea is to provide an integrated view of queries and related results, where both queries and results can be interactively manipulated and changes are immediately visualized. Furthermore, the relevance of queries and results can be gradually changed and thus it is possible for a user to explore effects even of slight query changes. Besides the interface itself, we present results of a first user study. The proposed interface can be applied in many interactive text retrieval scenarios. However, it can also be used to support decision making processes where an exploration and interpretation of complex data sets is required.

关键词： User interfaces

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Predicting New User's Behavior in Online Dating systems

Predicting New User's Behavior in Online Dating Systems

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7th International Conference on Advanced data Mining and Applications

作者： Wang, Tingting Liu, Hongyan He, Jun Jiang, Xuan Du, Xiaoyong Key Labs. of Data Engineering and Knowledge Engineering School of Information Renmin University of China 100872 China Department of Management Science and Engineering Tsinghua University 100084 China

ISBN: (纸本)9783642258558

Predicting new user's reaction behavior to its recommended candidate partner correctly is critical to improve recommendation accuracy in online dating systems. However, new user (cold start) problem and data sparseness problem in the online dating system make this task very challenging. In this paper, we propose a hybrid method called crowd wisdom based behavior prediction to solve the two problems and achieve good prediction accuracy. By this method, old users who have been recommended partners before are first separated into groups. Users in each group have similar preference for partners. Then, we propose a novel measure to combine a group user's collective behavior to predict one user's behavior, which can solve the data sparseness problem. By calculating the probability a new user belongs to each group and utilizing the group's behavior we can solve the new user problem. Based on these strategies. we develop a behavior prediction algorithm for new users. Experimental results conducted on a real online dating dataset show that our proposed method performs better than other traditional methods.

关键词： online dating recommendation clustering classification

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Reports of the AAAI 2011 conference workshops

Reports of the AAAI 2011 conference workshops

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作者： Agmon, Noa Agrawal, Vikas Aha, David W. Aloimonos, Yiannis Buckley, Donagh Doshi, Prashant Geib, Christopher Grasso, Floriana Green, Nancy Johnston, Benjamin Kaliski, Burt Kiekintveld, Christopher Law, Edith Lieberman, Henry Mengshoel, Ole J. Metzler, Ted Modayil, Joseph Oard, Douglas W. Onder, Nilufer O'Sullivan, Barry Pastra, Katerina Precup, Doina Ramachandran, Sowmya Reed, Chris Sariel-Talay, Sanem Selker, Ted Shastri, Lokendra Singh, Satinder Smith, Stephen F. Srivastava, Siddharth Sukthankar, Gita Uthus, David C. Williams, Mary-Anne Department of Computer Science University of Texas at Austin United States Center for Knowledge Driven Information Systems Infosys Labs India Adaptive Systems Section Naval Research Laboratory Washington DC United States Department of Computer Science University of Maryland College Park United States EMC's Center of Excellence in Ireland Research Europe at EMC Ireland Department of Computer Science University of Georgia United States School of Informatics University of Edinburgh United Kingdom Department of Computer Science University of Liverpool United Kingdom Department of Computer Science University of North Carolina Greensboro United States Faculty of Engineering and Information Technology University of Technology Sydney Australia VeriSign Inc. United States Department of Computer Science University of Texas at El Paso United States Machine Learning Department Carnegie Mellon University United States Massachusetts Institute of Technology Media Laboratory United States Carnegie Mellon University's Silicon Valley Campus United States Darrell W. Hughes Program for Religion and Science Dialogue Oklahoma City University United States Department of Computing Science University of Alberta Canada College of Information Studies Institute for Advanced Computer Studies University of Maryland College Park United States Department of Computer Science Michigan Technological University United States Department of Computer Science University College Cork Ireland Cognitive Systems Research Insitute Athens Greece School of Computer Science McGill University Canada Stottler Henke Inc. United States School of Computing University of Dundee United Kingdom Department of Computer Engineering Istanbul Technical University Turkey Convergence Lab Infosys Technologies Ltd. United States Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor United States Robotics Institute Carnegie Mellon University United States University of Wisconsin

The AAAI-11 workshop program was held Sunday and Monday, August 7-18, 2011, at the Hyatt Regency San Francisco in San Francisco, California USA. The AAAI-11 workshop program included 15 workshops covering a wide range of topics in artificial intelligence. The titles of the workshops were Activity Context Representation: Techniques and Languages;Analyzing Microtext;Applied Adversarial Reasoning and Risk Modeling;Artificial Intelligence and Smarter Living: The Conquest of Complexity;Artifiicial Intelligence for data Center Management and Cloud Computing;Automated Action Planning for Autonomous Mobile Robots;Computational Models of Natural Argument;Generalized Planning;Human Computation;Human-Robot Interaction in Elder Care;Interactive Decision Theory and Game Theory, 2010;Language-Action Tools for Cognitive Artificial Agents: Integrating Vision, Action, and Language;Lifelong Learning from Sensorimotor Experience;Plan, Activity, and Intent Recognition;and Scalable Integration of Analytics and Visualization. This article presents short summaries of those events. Copyright © 2012, Association for the Advancement of Artificial Intelligence. All rights reserved.

关键词： Human robot interaction

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Preface

Preface

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IEEE Workshop on Evolving and Adaptive Intelligent systems (EAIS)

作者： Plamen Angelov Dimitar Filev Nik Kasabov José Antonio Iglesias Communication Systems Department InfoLab21 Lancaster University LA1 4WA UK Intelligent Control & Information Systems Ford Research & Advanced Engineering 2101 Village Road MD #1437 Dearborn MI 48121 USA Knowledge Engineering and Discovery Research Institute School of Computing and Informatics Sciences Auckland University of Technology 581 Great South Rd 1020 New Zealand Carlos III University of Madrid Avda. Universidad 30 28911 Leganés Spain

An important research challenge that needs to be address in the area of intelligent systems is the development of new, innovative and original methods, algorithms and implementations of systems with a high level of intelligent; that is, with a high level of flexibility and autonomy. This intelligence needs to be developed by understanding the environment in which these systems operate. However, these environments could be non-stationary, unpredictably changing and partially or completely unknown. For this reason, in order to develop an intelligent system - able to face with problems such as modeling, control, prediction, classification or data mining - in such environments, they need to be able to evolve, to self-develop, to self-organize, to self-evaluate and to self-improve. This is the cornerstone behind the Evolving and Adaptive Intelligent systems.

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