Markov Decision Processes (MDP) have been widely used as a framework for planning under uncertainty. They allow to compute optimal sequences of actions in order to achieve a given...
To be autonomous, intelligent robots must learn the foundations of commonsense knowledge from their own sensorimotor experience in the world. We describe four recent research resu...
Benjamin Kuipers, Patrick Beeson, Joseph Modayil, ...
In this paper, partial knowledge about the possible transitions which can take place in a dynamical environment is represented by a set of pairs of propositional formulae, with th...
AI planning solves the problem of generating a correct and efficient ordered set of instantiated activities, from a knowledge base of generic actions, which when executed will tra...
The premises of this paper are 1) security is application dependent because application semantics directly influence proper protection; but 2) applications are generally too compl...