This paper examines the problem of finding an optimal policy for a Partially Observable Markov Decision Process (POMDP) when the model is not known or is only poorly specified. W...
: Data filtering is an important approach to reduce energy consumption. Following this idea, Interest is used as a constraint to filter uninterested data in sensor networks. Within...
—We address the issue of optimal energy allocation and admission control for communications satellites in earth orbit. Such satellites receive requests for transmission as they o...
Abstract. This paper describes a highly modular hierarchical behaviorbased control system for robots. Key features of the architecture include: easy addition/removal of behaviors, ...
Reinforcement Learning (RL) is a simulation-based technique useful in solving Markov decision processes if their transition probabilities are not easily obtainable or if the probl...