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From Infinite to Finite Programs: Explicit Error Bounds with Applications to Approximate Dynamic Programming

Publications associées (89)

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Single machine scheduling with scenarios

Ola Nils Anders Svensson

In the field of robust optimization, the goal is to provide solutions to combinatorial problems that hedge against variations of the numerical parameters. This constitutes an effort to design algorithms that are applicable in the presence of uncertainty in ...

2013

DynaProg for Scala

Thierry Coppey

Dynamic programming is an algorithmic technique to solve problems that follow the Bellman’s principle: optimal solutions depends on optimal sub-problem solutions. The core idea behind dynamic programming is to memoize intermediate results into matrices to ...

2013

Completeness and Ambiguity of Schema Cover

Karl Aberer, Quoc Viet Hung Nguyen, Zoltán Miklós

Given a schema and a set of concepts, representative of entities in the domain of discourse, schema cover deﬁnes correspondences between concepts and parts of the schema. Schema cover aims at interpreting the schema in terms of concepts and thus, vastly si ...

2013

Stochastic system controller synthesis for reachability specifications encoded by random sets

Maryam Kamgarpour, John Lygeros

We consider a reach–avoid specification for a stochastic hybrid dynamical system defined as reaching a goal set at some finite time, while avoiding an unsafe set at all previous times. In contrast with earlier works which consider the target and avoid sets ...

2013

A stochastic games framework for verification and control of discrete time stochastic hybrid systems

Maryam Kamgarpour, John Lygeros

We describe a framework for analyzing probabilistic reachability and safety problems for discrete time stochastic hybrid systems within a dynamic games setting. In particular, we consider finite horizon zero-sum stochastic games in which a control has the ...

2013

Mean Field for Markov Decision Processes: from Discrete to Continuous Optimization

Jean-Yves Le Boudec, Nicolas Gabriel Gast

We study the convergence of Markov decision processes, composed of a large number of objects, to optimization problems on ordinary differential equations. We show that the optimal reward of such a Markov decision process, which satisfies a Bellman equation ...

Institute of Electrical and Electronics Engineers2012

On the Use of Models for Real-Time Optimization

Dominique Bonvin

The operation of dynamic processes can be optimized using models that predict the system behavior well, in particular its optimality features. In practice, however, process models are often structurally inaccurate, and on-line adaptation is typically requi ...

2012

Robust resource allocations in temporal networks

Daniel Kuhn, Wolfram Wiesemann

Temporal networks describe workflows of time-consuming tasks whose processing order is constrained by precedence relations. In many cases, the durations of the network tasks can be influenced by the assignment of resources. This leads to the problem of sel ...

2012

Container Terminal Management

Ilaria Vacca

This thesis deals with models and methods for large scale optimization problems; in particular, we focus on decision problems arising in the context of seaport container terminals for the efficient management of terminal operations. Large-scale optimizatio ...

EPFL2011

A mean field approach for optimization in discrete time

Nicolas Gabriel Gast

This paper investigates the limit behavior of Markov decision processes made of independent objects evolving in a common environment, when the number of objects (N) goes to infinity. In the finite horizon case, we show that when the number of objects becom ...

2011