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ICML
2005
IEEE
16 years 4 months ago
Bounded real-time dynamic programming: RTDP with monotone upper bounds and performance guarantees
MDPs are an attractive formalization for planning, but realistic problems often have intractably large state spaces. When we only need a partial policy to get from a fixed start s...
H. Brendan McMahan, Maxim Likhachev, Geoffrey J. G...
IROS
2009
IEEE
206views Robotics» more  IROS 2009»
15 years 10 months ago
Bayesian reinforcement learning in continuous POMDPs with gaussian processes
— Partially Observable Markov Decision Processes (POMDPs) provide a rich mathematical model to handle realworld sequential decision processes but require a known model to be solv...
Patrick Dallaire, Camille Besse, Stéphane R...
IJCNN
2008
IEEE
15 years 10 months ago
Long-term prediction of time series using NNE-based projection and OP-ELM
Abstract— This paper proposes a combination of methodologies based on a recent development –called Extreme Learning Machine (ELM)– decreasing drastically the training time of...
Antti Sorjamaa, Yoan Miche, Robert Weiss, Amaury L...
CSB
2005
IEEE
223views Bioinformatics» more  CSB 2005»
15 years 9 months ago
Automatic Protein Function Annotation through Candidate Ortholog Clusters from Incomplete Genomes
Annotation of protein function often arises in the context of partially complete genomes but is not adequately addressed. We present an annotation method by extracting ortholog cl...
Akshay Vashist, Casimir A. Kulikowski, Ilya B. Muc...
IJCAI
2007
15 years 5 months ago
Analogical Learning in a Turn-Based Strategy Game
A key problem in playing strategy games is learning how to allocate resources effectively. This can be a difficult task for machine learning when the connections between actions a...
Thomas R. Hinrichs, Kenneth D. Forbus