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» PWL approximation of dynamical systems: an example
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AMC
2008
99views more  AMC 2008»
13 years 7 months ago
Markov chain network training and conservation law approximations: Linking microscopic and macroscopic models for evolution
In this paper, a general framework for the analysis of a connection between the training of artificial neural networks via the dynamics of Markov chains and the approximation of c...
Roderick V. N. Melnik
JSCIC
2008
107views more  JSCIC 2008»
13 years 7 months ago
A Hierarchy of Approximations of the Master Equation Scaled by a Size Parameter
Solutions of the master equation are approximated using a hierarchy of models based on the solution of ordinary differential equations: the macroscopic equations, the linear noise...
Lars Ferm, Per Lötstedt, Andreas Hellander
ATAL
2009
Springer
13 years 5 months ago
Replicator Dynamics for Multi-agent Learning: An Orthogonal Approach
Today's society is largely connected and many real life applications lend themselves to be modeled as multi-agent systems. Although such systems as well as their models are d...
Michael Kaisers, Karl Tuyls
HYBRID
2000
Springer
13 years 11 months ago
A Dynamic Bayesian Network Approach to Tracking Using Learned Switching Dynamic Models
Abstract. Switching linear dynamic systems (SLDS) attempt to describe a complex nonlinear dynamic system with a succession of linear models indexed by a switching variable. Unfortu...
Vladimir Pavlovic, James M. Rehg, Tat-Jen Cham
ATAL
2008
Springer
13 years 9 months ago
Approximate predictive state representations
Predictive state representations (PSRs) are models that represent the state of a dynamical system as a set of predictions about future events. The existing work with PSRs focuses ...
Britton Wolfe, Michael R. James, Satinder P. Singh