Approximate inference in dynamic systems is the problem of estimating the state of the system given a sequence of actions and partial observations. High precision estimation is fu...
In this paper, we introduce a new heuristic search algorithm based on mean values for anytime planning, called MHSP. It consists in associating the principles of UCT, a bandit-base...
We consider a fundamental flow maximization problem that arises during the evaluation of multiple overlapping queries defined on a data stream, in a heterogenous parallel environm...
In this paper we describe IPSS (Integrated Planning and Scheduling System), a domain independent solver that integrates an AI heuristic planner, that synthesizes courses of actions...
We present an argumentation-based formalism that an agent could use for constructing plans. We will analyze the interaction of arguments and actions when they are combined to cons...