In this paper, we continue our study of learning the kernel. We present a reformulation of this problem within a feature space environment. This leads us to study regularization in the dual space of all continuous functions on a compact domain with values in a Hilbert space with a mix norm. We also relate this problem in a special case to regularization. 1This work was supported by NSF Grant IT...

In this paper, a multi-period and multi-resource operating room (OR) scheduling and rescheduling problem with elective and semi-elective (semi-urgent) patients is addressed. A scheduling-rescheduling framework based on the so-called rolling horizon approach is proposed to solve the problem. The core of the proposed framework is a novel proposed mixed-integer linear programming (MILP) model with...

A real-time AI problem solver performs a task or a set of tasks in two phases: planning and execution. Under real-time constraints, a real-time AI problem solver must balance the planning and the execution phases of its operation to comply with deadlines. This paper provides a methodology for specification and analysis of real-time AI problems and problem solvers. This methodology is demonstrat...

Diagnosis of discrete event systems amounts to finding good explanations, in the form of system trajectories consistent with a given set of partially ordered observations. This problem is closely related to planning, and in fact can be recast as a classical planning problem. We formulate a PDDL encoding of this diagnosis problem, and use it to evaluate planners representing a variety of plannin...

The motion planning problem for an object with two degrees of freedom moving in the plane can be stated as follows: Given a set of polygonal obstacles in the plane, and a two-dimensional mobile object B with two degrees of freedom, determine if it is possible to move B from a start position to a nal position while avoiding the obstacles. If so, plan a path for such a motion. Techniques from com...

There has been a recent rise in research on real-time problem solving algorithms in artificial intelligence (AI). A real-time AI problem solver performs a task or a set of tasks in two phases. During the first phase, the problem solver searches for a solution that, once executed, will satisfy the requirements of the task. We refer to this phase as the planning phase or the search phase. During ...

There is a real need among researchers and students for pedagogical resources. In France, information retrieval techniques have been developed, for example in the Doc'CISMeF web site. As Pubmed, documents are indexed with (French) MeSH terms, one of the problems discovered, in quality studies, is the inadequacies between the user requests and the MeSH controlled vocabulary. Moreover, French (bu...

We propose an algorithmic framework for efficient anytime motion planning on large dense geometric roadmaps, in domains where collision checks and therefore edge evaluations are computationally expensive. A large dense roadmap (graph) can typically ensure the existence of high quality solutions for most motion-planning problems, but the size of the roadmap, particularly in high-dimensional spac...

this paper is a research on the ordering planning of a supply chain with one supplier, multi buyer and multi deteriorating items. items have fixed life time and expire dates. the ordering period is taken as variable and must be computed the proposed models. the problem is studied via two different approaches the first is the joint replenishment, based on the hwang and chew's model [3] and ...