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AAAI
2010
15 years 8 months ago
To Max or Not to Max: Online Learning for Speeding Up Optimal Planning
It is well known that there cannot be a single "best" heuristic for optimal planning in general. One way of overcoming this is by combining admissible heuristics (e.g. b...
Carmel Domshlak, Erez Karpas, Shaul Markovitch
IJCAI
2007
15 years 8 months ago
Learning Semantic Descriptions of Web Information Sources
The Internet is full of information sources providing various types of data from weather forecasts to travel deals. These sources can be accessed via web-forms, Web Services or RS...
Mark James Carman, Craig A. Knoblock
AAAI
1994
15 years 8 months ago
Learning to Select Useful Landmarks
To navigate effectively, an autonomous agent must be able to quickly and accurately determine its current location. Given an initial estimate of its position (perhaps based on dea...
Russell Greiner, Ramana Isukapalli
CEC
2010
IEEE
15 years 7 months ago
Two novel Ant Colony Optimization approaches for Bayesian network structure learning
Learning Bayesian networks from data is an N-P hard problem with important practical applications. Several researchers have designed algorithms to overcome the computational comple...
Yanghui Wu, John A. W. McCall, David W. Corne
CORR
2008
Springer
107views Education» more  CORR 2008»
15 years 6 months ago
A Spectral Algorithm for Learning Hidden Markov Models
Hidden Markov Models (HMMs) are one of the most fundamental and widely used statistical tools for modeling discrete time series. In general, learning HMMs from data is computation...
Daniel Hsu, Sham M. Kakade, Tong Zhang