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» Dynamic abstraction in reinforcement learning via clustering
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IROS
2008
IEEE
165views Robotics» more  IROS 2008»
15 years 4 months ago
Mutual development of behavior acquisition and recognition based on value system
Abstract. Both self-learning architecture (embedded structure) and explicit/implicit teaching from other agents (environmental design issue) are necessary not only for one behavior...
Yasutake Takahashi, Yoshihiro Tamura, Minoru Asada
IICAI
2007
14 years 11 months ago
Modeling Temporal Behavior via Structured Hidden Markov Models: an Application to Keystroking Dynamics
Structured Hidden Markov Models (S-HMM) are a variant of Hierarchical Hidden Markov Models; it provides an abstraction mechanism allowing a high level symbolic description of the k...
Ugo Galassi, Attilio Giordana, Charbel Julien, Lor...
CLUSTER
2007
IEEE
15 years 1 months ago
Identifying energy-efficient concurrency levels using machine learning
Abstract-- Multicore microprocessors have been largely motivated by the diminishing returns in performance and the increased power consumption of single-threaded ILP microprocessor...
Matthew Curtis-Maury, Karan Singh, Sally A. McKee,...
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TSMC
2008
135views more  TSMC 2008»
14 years 9 months ago
Wholesale Power Price Dynamics Under Transmission Line Limits: A Use of an Agent-Based Intelligent Simulator
Abstract--This research proposes a use of an agent-based intelligent simulator to numerically examine the influence of a transmission line limit on the dynamics of a wholesale powe...
Toshiyuki Sueyoshi, Gopalakrishna Reddy Tadiparthi
ECML
2007
Springer
15 years 3 months ago
Spectral Clustering and Embedding with Hidden Markov Models
Abstract. Clustering has recently enjoyed progress via spectral methods which group data using only pairwise affinities and avoid parametric assumptions. While spectral clustering ...
Tony Jebara, Yingbo Song, Kapil Thadani