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AI
2009
Springer
16 years 1 months ago
Grid-Enabled Adaptive Metamodeling and Active Learning for Computer Based Design
Many complex, real world phenomena are difficult to study directly using controlled experiments. Instead, the use of computer simulations has become commonplace as a feasible alte...
Dirk Gorissen
IEEECIT
2006
IEEE
16 years 15 days ago
Adaptive Routing for Sensor Networks using Reinforcement Learning
Efficient and robust routing is central to wireless sensor networks (WSN) that feature energy-constrained nodes, unreliable links, and frequent topology change. While most existi...
Ping Wang, Ting Wang
ACMACE
2007
ACM
15 years 10 months ago
Motivated reinforcement learning for adaptive characters in open-ended simulation games
Recently a new generation of virtual worlds has emerged in which users are provided with open-ended modelling tools with which they can create and modify world content. The result...
Kathryn Elizabeth Merrick, Mary Lou Maher
CVPR
2012
IEEE
13 years 9 months ago
Batch mode Adaptive Multiple Instance Learning for computer vision tasks
Multiple Instance Learning (MIL) has been widely exploited in many computer vision tasks, such as image retrieval, object tracking and so on. To handle ambiguity of instance label...
Wen Li, Lixin Duan, Ivor Wai-Hung Tsang, Dong Xu
KI
2002
Springer
15 years 6 months ago
Adaptivity through Unobstrusive Learning
In this paper, we present an approach for learning interest profiles implicitly from positive user observations only. This approach eliminates the need to prompt users for ratings...
Ingo Schwab, Alfred Kobsa