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» Dealing with stochastic reachability
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AIPS
2008
13 years 10 months ago
Stochastic Enforced Hill-Climbing
Enforced hill-climbing is an effective deterministic hillclimbing technique that deals with local optima using breadth-first search (a process called "basin flooding"). ...
Jia-Hong Wu, Rajesh Kalyanam, Robert Givan
TROB
2010
129views more  TROB 2010»
13 years 6 months ago
A Probabilistic Particle-Control Approximation of Chance-Constrained Stochastic Predictive Control
—Robotic systems need to be able to plan control actions that are robust to the inherent uncertainty in the real world. This uncertainty arises due to uncertain state estimation,...
Lars Blackmore, Masahiro Ono, Askar Bektassov, Bri...
ISMB
1994
13 years 9 months ago
Stochastic Motif Extraction Using Hidden Markov Model
In this paper, westudy the application of an ttMM(hidden Markov model) to the problem of representing protein sequencesby a stochastic motif. Astochastic protein motif represents ...
Yukiko Fujiwara, Minoru Asogawa, Akihiko Konagaya
BMCBI
2008
77views more  BMCBI 2008»
13 years 7 months ago
Stochastic models for the in silico simulation of synaptic processes
Background: Research in life sciences is benefiting from a large availability of formal description techniques and analysis methodologies. These allow both the phenomena investiga...
Andrea Bracciali, Marcello Brunelli, Enrico Catald...
ECCV
2002
Springer
14 years 9 months ago
A Stochastic Algorithm for 3D Scene Segmentation and Reconstruction
In this paper, we present a stochastic algorithm by effective Markov chain Monte Carlo (MCMC) for segmenting and reconstructing 3D scenes. The objective is to segment a range image...
Feng Han, Zhuowen Tu, Song Chun Zhu