Probabilistically valid stochastic extensions of deterministic models for systems with uncertainty
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Title
Probabilistically valid stochastic extensions of deterministic models for systems with uncertainty
Authors
Keywords
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Journal
INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH
Volume 34, Issue 10, Pages 1278-1295
Publisher
SAGE Publications
Online
2015-05-29
DOI
10.1177/0278364915576336
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- (2008) J. Proctor et al. REGULAR & CHAOTIC DYNAMICS
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