In sequential decision-making problems formulated as Markov decision processes, state-value function approximation using domain features is a critical technique for scaling up the...
Abstract. We present a model for the multiagent patrolling problem with continuous-time. An anytime and online algorithm is then described and extended to asynchronous multiagent d...
Recent adaptive image interpretation systems can reach optimal performance for a given domain via machine learning, without human intervention. The policies are learned over an ex...
Although a partially observable Markov decision process (POMDP) provides an appealing model for problems of planning under uncertainty, exact algorithms for POMDPs are intractable...
In this paper, we address the problem of providing a service broker, which offers to prospective users a composite service with a range of different Quality of Service (QoS) class...
Marco Abundo, Valeria Cardellini, Francesco Lo Pre...