13 research outputs found

    A History of Participation in Museums and Archives

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    Traversing disciplines, A History of Participation in Museums and Archives provides a framework for understanding how participatory modes in natural, cultural, and scientific heritage institutions intersect with practices in citizen science and citizen humanities. Drawing on perspectives in cultural history, science and technology studies, and media and communication theory, the book explores how museums and archives make science and cultural heritage relevant to people’s everyday lives, while soliciting their assistance and participation in research and citizen projects. More specifically, the book critically examines how different forms of engagement are constructed, how concepts of democratization are framed and enacted, and how epistemic practices in science and the humanities are transformed through socio-technological infrastructures. Tracking these central themes across disciplines and research from Europe, Canada, Australia and the United States, the book simultaneously considers their relevance for museum and heritage studies. A History of Participation in Museums and Archives should be essential reading for a broad academic audience, including scholars and students in museum and heritage studies, digital humanities, and the public communication of science and technology. It should also be of great interest to museum professionals working to foster public engagement through collaboration with networks and local community groups

    Building a Believable and Effective Agent for a 3D Boxing Simulation Game

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    Abstract-This paper describes an approach used to build and optimize a practical AI solution for a 3D boxing simulation game. The two main features of the designed AI agent are believability (human-likeness of agent's behavior) and effectiveness (agent's capability to reach own goals). We show how learning by observation and case-based reasoning techniques are used to create believable behavior. Then we employ reinforcement learning to optimize agent's behavior, turning the agent into a strong opponent, acting in a commercial-level game environment. The used knowledge representation scheme supports high maintainability, important for game developers. Keywords-believability; behavior capture; learning by observation; reinforcement learning. INTRODUCTION The quality of a virtual agent is usually associated with its effectiveness in reaching own goals. In these terms, an agent that plays chess at grandmaster level is better than an average-skilled AI player. However, in the domain of computer simulation and video games, the factor of believability [1] also turns out to be one of the key factors of a successful AI. According to [1], a believable agent "provides the illusion of life, and thus permits the audience's suspension of disbelief". Such an agent normally possesses certain human-like features: it can learn, make mistakes, and adjust own strategy to be effective against a particular opponent. Believability is recognized as an important factor both by researchers and by game developers [2; 3]. A number of recent research projects are devoted to the creation of believable agents for video game environments In our recent wor

    Preface

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    Enhancing Free-text Interactions in a Communication Skills Learning Environment

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    Learning environments frequently use gamification to enhance user interactions.Virtual characters with whom players engage in simulated conversations often employ prescripted dialogues; however, free user inputs enable deeper immersion and higher-order cognition. In our learning environment, experts developed a scripted scenario as a sequence of potential actions, and we explore possibilities for enhancing interactions by enabling users to type free inputs that are matched to the pre-scripted statements using Natural Language Processing techniques. In this paper, we introduce a clustering mechanism that provides recommendations for fine-tuning the pre-scripted answers in order to better match user inputs

    24th International Conference on Information Modelling and Knowledge Bases

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    In the last three decades information modelling and knowledge bases have become essentially important subjects not only in academic communities related to information systems and computer science but also in the business area where information technology is applied. The series of European – Japanese Conference on Information Modelling and Knowledge Bases (EJC) originally started as a co-operation initiative between Japan and Finland in 1982. The practical operations were then organised by professor Ohsuga in Japan and professors Hannu Kangassalo and Hannu Jaakkola in Finland (Nordic countries). Geographical scope has expanded to cover Europe and also other countries. Workshop characteristic - discussion, enough time for presentations and limited number of participants (50) / papers (30) - is typical for the conference. Suggested topics include, but are not limited to: 1. Conceptual modelling: Modelling and specification languages; Domain-specific conceptual modelling; Concepts, concept theories and ontologies; Conceptual modelling of large and heterogeneous systems; Conceptual modelling of spatial, temporal and biological data; Methods for developing, validating and communicating conceptual models. 2. Knowledge and information modelling and discovery: Knowledge discovery, knowledge representation and knowledge management; Advanced data mining and analysis methods; Conceptions of knowledge and information; Modelling information requirements; Intelligent information systems; Information recognition and information modelling. 3. Linguistic modelling: Models of HCI; Information delivery to users; Intelligent informal querying; Linguistic foundation of information and knowledge; Fuzzy linguistic models; Philosophical and linguistic foundations of conceptual models. 4. Cross-cultural communication and social computing: Cross-cultural support systems; Integration, evolution and migration of systems; Collaborative societies; Multicultural web-based software systems; Intercultural collaboration and support systems; Social computing, behavioral modeling and prediction. 5. Environmental modelling and engineering: Environmental information systems (architecture); Spatial, temporal and observational information systems; Large-scale environmental systems; Collaborative knowledge base systems; Agent concepts and conceptualisation; Hazard prediction, prevention and steering systems. 6. Multimedia data modelling and systems: Modelling multimedia information and knowledge; Contentbased multimedia data management; Content-based multimedia retrieval; Privacy and context enhancing technologies; Semantics and pragmatics of multimedia data; Metadata for multimedia information systems. Overall we received 56 submissions. After careful evaluation, 16 papers have been selected as long paper, 17 papers as short papers, 5 papers as position papers, and 3 papers for presentation of perspective challenges. We thank all colleagues for their support of this issue of the EJC conference, especially the program committee, the organising committee, and the programme coordination team. The long and the short papers presented in the conference are revised after the conference and published in the Series of “Frontiers in Artificial Intelligence” by IOS Press (Amsterdam). The books “Information Modelling and Knowledge Bases” are edited by the Editing Committee of the conference. We believe that the conference will be productive and fruitful in the advance of research and application of information modelling and knowledge bases. Bernhard Thalheim Hannu Jaakkola Yasushi Kiyok

    Benchmarky pro projekt Pogamut

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    Práca sa zaoberá tvorbou a použitím testovacích prostredí pre pocítacom ovládaných agentov (botov) do hry Unreal Tournament 2004. V prvej casti sa snaží identifikovat klúcové prvky botov, ktoré je možné exaktne testovat v prostredí hry a následne vyhodnocovat ich efektivitu. Druhá cast spocíva v návrhu a tvorbe prostredí, v ktorých by sa vybrané prvky otestovali. Cielom tretej casti je vytvorenie referencných botov pre jednotlivé prostredia, ktorí budú slúžit ako základ pre budúci vývoj.In the present work we design and develop the benchmarks for the computer controlled agents (bots) into the game Unreal Tournament 2004. In the first part of the work, we try to identify the most important aspects of the bots which should be tested. In the second part we design and develop the environments for testing the selected aspects. In the third part we implement the reference solutions (bots) for each of the created environments.Department of Software and Computer Science EducationKatedra softwaru a výuky informatikyFaculty of Mathematics and PhysicsMatematicko-fyzikální fakult
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