In many practical reinforcement learning problems, the state space is too large to permit an exact representation of the value function, much less the time required to compute it. ...
The design of computer architectures requires the setting of multiple parameters on which the final performance depends. The number of possible combinations make an extremely huge ...
Pedro A. Castillo, Antonio Miguel Mora, Juan Juli&...
We consider the task of assigning experts from a portfolio of specialists in order to solve a set of tasks. We apply a Bayesian model which combines collaborative filtering with a...
David H. Stern, Horst Samulowitz, Ralf Herbrich, T...
Dimensionality reduction is the process by which a set of data points in a higher dimensional space are mapped to a lower dimension while maintaining certain properties of these p...
In cooperative multiagent systems an alternative that maximizes the social welfare--the sum of utilities--can only be selected if each agent reports its full utility function. Thi...