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» Approximate predictive state representations
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HYBRID
2007
Springer
16 years 2 days 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
15 years 7 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
15 years 10 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»
15 years 5 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
15 years 11 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