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GECCO
2004
Springer
142views Optimization» more  GECCO 2004»
14 years 3 months ago
Improving MACS Thanks to a Comparison with 2TBNs
Abstract. Factored Markov Decision Processes is the theoretical framework underlying multi-step Learning Classifier Systems research. This framework is mostly used in the context ...
Olivier Sigaud, Thierry Gourdin, Pierre-Henri Wuil...
WCNC
2010
IEEE
14 years 1 months ago
Modeling IEEE 802.11 DCF System Dynamics
—Experiments show that IEEE 802.11 DCF system exhibits unstable behavior in the congestion onset load range where the system starts to become saturated. This phenomenon is not we...
Zhenzhen Cao, Ren Ping Liu, Xun Yang, Yang Xiao
DMSN
2008
ACM
13 years 11 months ago
Probabilistic processing of interval-valued sensor data
When dealing with sensors with different time resolutions, it is desirable to model a sensor reading as pertaining to a time interval rather than a unit of time. We introduce two ...
Sander Evers, Maarten M. Fokkinga, Peter M. G. Ape...
PERCOM
2003
ACM
14 years 3 months ago
Recognition of Human Activity through Hierarchical Stochastic Learning
Seeking to extend the functional capability of the elderly, we explore the use of probabilistic methods to learn and recognise human activity in order to provide monitoring suppor...
Sebastian Lühr, Hung Hai Bui, Svetha Venkates...
ICANN
2001
Springer
14 years 2 months ago
Market-Based Reinforcement Learning in Partially Observable Worlds
Unlike traditional reinforcement learning (RL), market-based RL is in principle applicable to worlds described by partially observable Markov Decision Processes (POMDPs), where an ...
Ivo Kwee, Marcus Hutter, Jürgen Schmidhuber