Search Results - Computing methodologies Machine learning Machine learning approaches Stochastic games*

Multi-Structural Games and Number of Quantifiers by Fagin, Ronald, Lenchner, Jonathan, Regan, Kenneth W., Vyas, Nikhil

“…We study multi-structural games, played on two sets {\mathcal{A}} and {\mathcal{B}} of structures. These games generalize Ehrenfeucht-Fraïssé games. Whereas…”
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Markov decision process routing games by Calderone, Dan, Sastry, S. Shankar

“… This work can be thought of as a routing-game-based formulation of continuous population stochastic games…”
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A peer-to-peer simulation technique for instanced massively multiplayer games by Cecin, Fabio Reis, Geyer, Claudio Fernando Resin, Rabello, Solon, Barbosa, Jorge Luis Victoria

“…We propose a peer-to-peer event ordering and simulation technique aimed at networked real-time action games. Partially based on replicated simulators, its goal…”
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The Distinctive Challenges of Pervasive Games as Distributed Real-Time Applications by Benford, Steve

“… From the city streets to the remote wilderness, players with mobile computing devices move through the world, sensors capture information about their current context, including their location…”
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How Relevant is Game Theory to Intelligent Agent Technology? by Shoham, Professor Yoav

“…At this point, restricted to rather specialized areas, and even there must be taken with a grain of salt. But at the same time you can't afford not to know it;…”
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Designing the Market Game for a Commodity Trading Simulation by Cheng, Shih-Fen

“…In this paper, we propose to design a market game that (a) can be used in modeling and studying commodity trading scenarios, and (b) can be used in capturing…”
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Social Collaboration, Stochastic Strategies and Information Referrals by Nowostawski, Mariusz, Foukia, Noria

“…Referrals are used in multi-agent systems, network agents and peer-to-peer systems for the purpose of global or local information spreading to facilitate trust…”
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A Game Theoretic Approach to Active Distributed Data Mining by Zhang, Xiaofeng, Cheung, William K.

“…Learning-from-abstraction(LFA) is a recently proposed model-based distributed data mining approach which aims to the mining process both scalable and privacy preserving…”
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Modeling as Craft by Fishwick, Paul

“…Toy boats, automobiles, and planesare models that entertain and delight us inchildhood. As we grow, we might availourselves of more advanced models that…”
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Path lookahead: a data flow view of PDES models by Meyer, Richard A., Bargrodia, Rajive L.

“…Architectural advances are making PDES more difficult. Processor speed improves much more quickly than interprocessor communication and memory. Lagging memory…”
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