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» Generalization Improvement in Multi-Objective Learning
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IJCAI
2007
13 years 10 months ago
Bayesian Inverse Reinforcement Learning
Inverse Reinforcement Learning (IRL) is the problem of learning the reward function underlying a Markov Decision Process given the dynamics of the system and the behaviour of an e...
Deepak Ramachandran, Eyal Amir
AAAI
2012
11 years 11 months ago
Learning the Kernel Matrix with Low-Rank Multiplicative Shaping
Selecting the optimal kernel is an important and difficult challenge in applying kernel methods to pattern recognition. To address this challenge, multiple kernel learning (MKL) ...
Tomer Levinboim, Fei Sha
ICML
2006
IEEE
14 years 9 months ago
Learning the structure of Factored Markov Decision Processes in reinforcement learning problems
Recent decision-theoric planning algorithms are able to find optimal solutions in large problems, using Factored Markov Decision Processes (fmdps). However, these algorithms need ...
Thomas Degris, Olivier Sigaud, Pierre-Henri Wuille...
ICRA
2009
IEEE
179views Robotics» more  ICRA 2009»
14 years 3 months ago
Automatic weight learning for multiple data sources when learning from demonstration
— Traditional approaches to programming robots are generally inaccessible to non-robotics-experts. A promising exception is the Learning from Demonstration paradigm. Here a polic...
Brenna Argall, Brett Browning, Manuela M. Veloso
SIGUCCS
2003
ACM
14 years 2 months ago
The technology learning center (TLC): a comprehensive learning environment for students
As technology becomes more pervasive in our lives, and continues to change rapidly, it is essential for college students to have opportunities to improve their computer abilities ...
Sheree Kornkven