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-This is an efficient, C++ implementation of the Bayesian optimization
-algorithm presented in the papers:
+This is an efficient, C++ implementation of several Bayesian optimization
+algorithms. See References for some of the papers.
-Ruben Martinez-Cantin, Nando de Freitas, Arnaud Doucet and Jose Castellanos.
-Active Policy Learning for Robot Planning and Exploration under Uncertainty 
-Robotics: Science and Systems. 2007
+Basically, it combines the use of an stochastic process as a surrogate function
+with the use of some "active learning" criterion. to find the optimum an "arbitrary" 
+function using very few iterations.
-Ruben Martinez-Cantin, Nando de Freitas, Eric Brochu, Jose Castellanos and 
-Arnaud Doucet (2009) A Bayesian Exploration-Exploitation Approach for 
-Optimal Online Sensing and Planning with a Visually Guided Mobile Robot. 
-Autonomous Robots - Special Issue on Robot Learning, Part B, 27(3):93-103.
-Basically, it uses the active learning strategy to optimize an "arbitrary" 
-funtion using few iterations.
+It can also be used for sequential experimental design and stochastic bandits by
+changing the criterion.
+4-[[Known Issues]]
 === 1 - INSTALL: ===