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» How to Dynamically Merge Markov Decision Processes
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IROS
2006
IEEE
202views Robotics» more  IROS 2006»
15 years 3 months ago
Topological characterization of mobile robot behavior
— We propose to classify the behaviors of a mobile robot thanks to topological methods as an alternative to metric ones. To do so, we adapt an analysis scheme from Physics of non...
Aurélien Hazan, Frédéric Dave...
SIGMETRICS
2010
ACM
195views Hardware» more  SIGMETRICS 2010»
15 years 1 months ago
CWS: a model-driven scheduling policy for correlated workloads
We define CWS, a non-preemptive scheduling policy for workloads with correlated job sizes. CWS tackles the scheduling problem by inferring the expected sizes of upcoming jobs bas...
Giuliano Casale, Ningfang Mi, Evgenia Smirni
CODES
2009
IEEE
15 years 26 days ago
An MDP-based application oriented optimal policy for wireless sensor networks
Technological advancements due to Moore’s law have led to the proliferation of complex wireless sensor network (WSN) domains. One commonality across all WSN domains is the need ...
Arslan Munir, Ann Gordon-Ross
TON
2002
112views more  TON 2002»
14 years 9 months ago
Pricing in multiservice loss networks: static pricing, asymptotic optimality, and demand substitution effects
We consider a communication network with fixed routing that can accommodate multiple service classes, differing in bandwidth requirements, demand pattern, call duration, and routin...
Ioannis Ch. Paschalidis, Yong Liu
NECO
2007
150views more  NECO 2007»
14 years 9 months ago
Reinforcement Learning, Spike-Time-Dependent Plasticity, and the BCM Rule
Learning agents, whether natural or artificial, must update their internal parameters in order to improve their behavior over time. In reinforcement learning, this plasticity is ...
Dorit Baras, Ron Meir