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IJCAI
2007
15 years 2 months ago
Using Linear Programming for Bayesian Exploration in Markov Decision Processes
A key problem in reinforcement learning is finding a good balance between the need to explore the environment and the need to gain rewards by exploiting existing knowledge. Much ...
Pablo Samuel Castro, Doina Precup
AAAI
2000
15 years 2 months ago
Decision Making under Uncertainty: Operations Research Meets AI (Again)
Models for sequential decision making under uncertainty (e.g., Markov decision processes,or MDPs) have beenstudied in operations research for decades. The recent incorporation of ...
Craig Boutilier
ICLP
1999
Springer
15 years 5 months ago
Logic Programming in Oz with Mozart
Oz is a multiparadigm language that supports logic programming as one of its major paradigms. A multiparadigm language is designed to support different programming paradigms (log...
Peter Van Roy
ICANNGA
2009
Springer
145views Algorithms» more  ICANNGA 2009»
15 years 7 months ago
Supporting Scalable Bayesian Networks Using Configurable Discretizer Actuators
We propose a generalized model with configurable discretizer actuators as a solution to the problem of the discretization of massive numerical datasets. Our solution is based on a ...
Isaac Olusegun Osunmakinde, Antoine B. Bagula
AAAI
2010
15 years 2 months ago
Efficient Spectral Feature Selection with Minimum Redundancy
Spectral feature selection identifies relevant features by measuring their capability of preserving sample similarity. It provides a powerful framework for both supervised and uns...
Zheng Zhao, Lei Wang, Huan Liu