The last few years have seen a renewal of interest in the consideration of dynamic programming in compiler technology. This is due to the compactness of the representations, which...
Manuel Vilares Ferro, Miguel A. Alonso, David Cabr...
This paper is concerned with developing an information-theoretic framework to aggregate the state space of a Hidden Markov Model (HMM) on discrete state and observation spaces. The...
Partially Observable Markov Decision Process models (POMDPs) have been applied to low-level robot control. We show how to use POMDPs differently, namely for sensorplanning in the ...
We introduce a new algorithm based on linear programming that approximates the differential value function of an average-cost Markov decision process via a linear combination of p...
We consider a problem domain where coalitions of agents are formed in order to execute tasks. Each task is assigned at most one coalition of agents, and the coalition can be reorg...