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ICML
1994
IEEE
15 years 10 months ago
Learning Without State-Estimation in Partially Observable Markovian Decision Processes
Reinforcement learning (RL) algorithms provide a sound theoretical basis for building learning control architectures for embedded agents. Unfortunately all of the theory and much ...
Satinder P. Singh, Tommi Jaakkola, Michael I. Jord...
ENTCS
2007
101views more  ENTCS 2007»
15 years 6 months ago
Systems Modelling via Resources and Processes: Philosophy, Calculus, Semantics, and Logic
We describe a programme of research in resource semantics, concurrency theory, bunched logic, and stochastic processes, as applied to mathematical systems modelling. Motivated by ...
David J. Pym, Chris M. N. Tofts
CCE
2004
15 years 6 months ago
A strategy for MINLP synthesis of flexible and operable processes
This paper presents a sequential two-stage strategy for the stochastic synthesis of chemical processes in which flexibility and ability to adjust manipulated variables are taken i...
Zorka Novak Pintaric, Zdravko Kravanja
ICRA
2010
IEEE
185views Robotics» more  ICRA 2010»
15 years 4 months ago
Heteroscedastic Gaussian processes for data fusion in large scale terrain modeling
This paper presents a novel approach to data fusion for stochastic processes that model spatial data. It addresses the problem of data fusion in the context of large scale terrain ...
Shrihari Vasudevan, Fabio T. Ramos, Eric Nettleton...
ECCV
2006
Springer
16 years 8 months ago
Cyclostationary Processes on Shape Spaces for Gait-Based Recognition
Abstract. We present a geometric and statistical approach to gaitbased human recognition. The novelty here is to consider observations of gait, considered as planar silhouettes, to...
David Kaziska, Anuj Srivastava