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ICML
2008
IEEE
16 years 5 months ago
Apprenticeship learning using linear programming
In apprenticeship learning, the goal is to learn a policy in a Markov decision process that is at least as good as a policy demonstrated by an expert. The difficulty arises in tha...
Umar Syed, Michael H. Bowling, Robert E. Schapire
ICML
2008
IEEE
16 years 5 months ago
Reinforcement learning with limited reinforcement: using Bayes risk for active learning in POMDPs
Partially Observable Markov Decision Processes (POMDPs) have succeeded in planning domains that require balancing actions that increase an agent's knowledge and actions that ...
Finale Doshi, Joelle Pineau, Nicholas Roy
PKDD
2009
Springer
129views Data Mining» more  PKDD 2009»
15 years 10 months ago
Considering Unseen States as Impossible in Factored Reinforcement Learning
Abstract. The Factored Markov Decision Process (FMDP) framework is a standard representation for sequential decision problems under uncertainty where the state is represented as a ...
Olga Kozlova, Olivier Sigaud, Pierre-Henri Wuillem...
DIGITEL
2007
IEEE
15 years 10 months ago
Shadow Box: an interactive learning toy for children
The Shadow Box is a tangible computing project that exploits visual association and auditory clues to teach children the representational relationship between words and their mean...
Ja-Young Sung, Aaron Levisohn, Ji-won Song, Ben To...
ECML
2007
Springer
15 years 10 months ago
An Unsupervised Learning Algorithm for Rank Aggregation
Many applications in information retrieval, natural language processing, data mining, and related fields require a ranking of instances with respect to a specified criteria as op...
Alexandre Klementiev, Dan Roth, Kevin Small