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ICML
2007
IEEE
15 years 10 months ago
On learning linear ranking functions for beam search
Beam search is used to maintain tractability in large search spaces at the expense of completeness and optimality. We study supervised learning of linear ranking functions for con...
Yuehua Xu, Alan Fern
ICML
1995
IEEE
15 years 10 months ago
Residual Algorithms: Reinforcement Learning with Function Approximation
A number of reinforcement learning algorithms have been developed that are guaranteed to converge to the optimal solution when used with lookup tables. It is shown, however, that ...
Leemon C. Baird III
DAC
2006
ACM
15 years 11 months ago
SAT sweeping with local observability don't-cares
SAT sweeping is a method for simplifying an AND/INVERTER graph (AIG) by systematically merging graph vertices from the inputs towards the outputs using a combination of structural...
Qi Zhu, Nathan Kitchen, Andreas Kuehlmann, Alberto...
ISCIS
2003
Springer
15 years 3 months ago
A New Continuous Action-Set Learning Automaton for Function Optimization
In this paper, we study an adaptive random search method based on continuous action-set learning automaton for solving stochastic optimization problems in which only the noisecorr...
Hamid Beigy, Mohammad Reza Meybodi
ICRA
2008
IEEE
113views Robotics» more  ICRA 2008»
15 years 4 months ago
Reinforcement learning with function approximation for cooperative navigation tasks
— In this paper, we propose a reinforcement learning approach to address multi-robot cooperative navigation tasks in infinite settings. We propose an algorithm to simultaneously...
Francisco S. Melo, M. Isabel Ribeiro