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» Approximate predictive state representations
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HYBRID
2007
Springer
14 years 1 months ago
Robust, Optimal Predictive Control of Jump Markov Linear Systems Using Particles
Hybrid discrete-continuous models, such as Jump Markov Linear Systems, are convenient tools for representing many real-world systems; in the case of fault detection, discrete jumps...
Lars Blackmore, Askar Bektassov, Masahiro Ono, Bri...
AAAI
1996
13 years 9 months ago
Computing Optimal Policies for Partially Observable Decision Processes Using Compact Representations
: Partially-observable Markov decision processes provide a very general model for decision-theoretic planning problems, allowing the trade-offs between various courses of actions t...
Craig Boutilier, David Poole
SIGGRAPH
1992
ACM
13 years 11 months ago
Predicting reflectance functions from complex surfaces
We describe a physically-based Monte Carlo technique for approximating bidirectional reflectance distribution functions (BRDFs) for a large class of geometries by directly simulat...
Stephen H. Westin, James Arvo, Kenneth E. Torrance
NN
1998
Springer
148views Neural Networks» more  NN 1998»
13 years 7 months ago
ARTMAP-IC and medical diagnosis: Instance counting and inconsistent cases
For complex database prediction problems such as medical diagnosis, the ARTMAP-IC neural network adds distributed prediction and category instance counting to the basic fuzzy ARTM...
Gail A. Carpenter, Natalya Markuzon
ATAL
2005
Springer
14 years 1 months ago
Improving reinforcement learning function approximators via neuroevolution
Reinforcement learning problems are commonly tackled with temporal difference methods, which use dynamic programming and statistical sampling to estimate the long-term value of ta...
Shimon Whiteson