Stochastic Shortest Path Problems (SSPs) are a common representation for probabilistic planning problems. Two approaches can be used to solve SSPs: (i) consider all probabilistically reachable states and (ii) plan only for a subset of these reachable states. Closed policies, the solutions obtained in the former approach, require significant computational effort, and they do not require replanni...

One way to approach end-to-end autonomous driving is to learn a policy function that maps from a sensory input, such as an image frame from a front-facing camera, to a driving action, by imitating an expert driver, or a reference policy. This can be done by supervised learning, where a policy function is tuned to minimize the difference between the predicted and ground-truth actions. A policy f...

We present an “opportunistic” transmission scheduling policy that exploits time-varying channel conditions and maximizes the system performance stochastically under a certain resource allocation constraint. We establish the optimality of the scheduling scheme, and also that every user experiences a performance improvement over any non-opportunistic scheduling policy when users have independent ...

With the evolution of QoS-capable third generation wireless networks, the wireless network community has been increasingly looking for a framework that can provide an effective, network independent, end-to-end QoS control. In this paper, we first construct such a framework and then describe how dynamic SLA-based control can be used to achieve end-to-end QoS in a wired and wireless (UMTS) enviro...

In system monitoring, one is often interested in checking properties of aggregated data. Current policy monitoring approaches are limited in the kinds of aggregations they handle. To rectify this, we extend an expressive language, metric first-order temporal logic, with aggregation operators. Our extension is inspired by the aggregation operators common in database query languages like SQL. We ...

Relying on non-enforceable normative language to persuade Web sites to make their privacy practices clear has proven unsuccessful, and where privacy policies are present, they are notoriously unclear and unread. Various machine-readable techniques have been proposed to address this problem, but many have suffered from practical difficulties. We propose a simple standard for transmitting policy ...

Flow Caml is an extension of the Objective Caml language with a type system tracing information flow. Its purpose is basically to allow to write “real” programs and to automatically check that they obey some confidentiality or integrity policy. In Flow Caml, standard ML types are annotated with security levels chosen in a user-definable lattice. Each annotation gives an approximation of the inf...

Welfare regimes across Europe differ considerably with respect to the support of and the policy instruments used to foster families with dependent children. In striving for a harmonization of social policy across EU-countries more insight in such cross-national differences is needed; this is especially true in light of the recent Eastern European extension of the EU. This paper adds to this res...

We propose a novel actor-critic algorithm with guaranteed convergence to an optimal policy for a discounted reward Markov decision process. The actor incorporates a descent direction that is motivated by the solution of a certain non-linear optimization problem. We also discuss an extension to incorporate function approximation and demonstrate the practicality of our algorithms on a network rou...

Policy, Health Resources and Services Administration, U.S. Department of Health and Human Services. The Rural Health Panel receives continuing support from RUPRI, the result of a Congressional Special Grant, administered through the Cooperative State Research, Education, and Extension Service, U.S. Department of Agriculture. REDESIGNING MEDICARE: CONSIDERATIONS FOR RURAL BENEFICIARIES AND HEALT...