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AIPS
2006
15 years 8 months ago
Combining Stochastic Task Models with Reinforcement Learning for Dynamic Scheduling
We view dynamic scheduling as a sequential decision problem. Firstly, we introduce a generalized planning operator, the stochastic task model (STM), which predicts the effects of ...
Malcolm J. A. Strens
NAR
2006
98views more  NAR 2006»
15 years 7 months ago
oGNM: online computation of structural dynamics using the Gaussian Network Model
An assessment of the equilibrium dynamics of biomolecular systems, and in particular their most cooperativefluctuationsaccessibleundernativestate conditions, is a first step towar...
Lee-Wei Yang, A. J. Rader, Xiong Liu, Christopher ...
ICPR
2010
IEEE
16 years 2 months ago
Probabilistic Modeling of Dynamic Traffic Flow across Non-Overlapping Camera Views
In this paper, we propose a probabilistic method to model the dynamic traffic flow across nonoverlapping camera views. By assuming the transition time of object movement follows a...
Ching-Chun Huang, Wei-Chen Chiu, Sheng-Jyh Wang, J...
ICMCS
2008
IEEE
118views Multimedia» more  ICMCS 2008»
16 years 1 months ago
A stochastic model of selective visual attention with a dynamic Bayesian network
Recent studies in signal detection theory suggest that the human responses to the stimuli on a visual display are nondeterministic. People may attend to different locations on the...
Derek Pang, Akisato Kimura, Tatsuto Takeuchi, Junj...
IEEEIAS
2008
IEEE
16 years 1 months ago
Dynamic Substitution Model
In this paper, we present the Dynamic Injection Model (DIM) and its variant the Static Injection Model (SIM). DIM is a model that allows any iterative block cipher to accept a var...
Mohamed Abo El-Fotouh, Klaus Diepold