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...
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 ...
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...
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...
— 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...