Publications de Thomas Léauté

Protecting Privacy through Distributed Computation in Multi-agent Decision Making

As large-scale theft of data from corporate servers is becoming increasingly common, it becomes interesting to examine alternatives to the paradigm of centralizing sensitive data into large databases. Instead, one could use cryptography and distributed com ...

AI Access Foundation2013

Distributed Constraint Optimization : Privacy Guarantees and Stochastic Uncertainty

Thomas Léauté

Distributed Constraint Satisfaction (DisCSP) and Distributed Constraint Optimization (DCOP) are formal frameworks that can be used to model a variety of problems in which multiple decision-makers cooperate towards a common goal: from computing an equilibri ...

EPFL2011

Distributed Constraint Optimization under Stochastic Uncertainty

Boi Faltings, Thomas Léauté

In many real-life optimization problems involving multiple agents, the rewards are not necessarily known exactly in advance, but rather depend on sources of exogenous uncertainty. For instance, delivery companies might have to coordinate to choose who shou ...

2011

Coordinating Logistics Operations with Privacy Guarantees

Boi Faltings, Thomas Léauté

Several logistics service providers serve a certain number of customers, geographically spread over an area of operations. They would like to coordinate their operations so as to minimize overall cost. At the same time, they would like to keep information ...

2011

Ensuring Privacy through Distributed Computation in Multiple-Depot Vehicle Routing Problems

Boi Faltings, Thomas Léauté, Brammert Ottens

The Vehicle Routing Problem (VRP) has been extensively studied over the last twenty years, because it is an abstraction of many real-life logistics problems. In its multiple-depot variant (MDVRP), the routes of vehicles located at various depots must be op ...

2010

Method to allocate inter-dependent resources by a set of participants

Boi Faltings, Adrian Petcu, Thomas Léauté

The object of the present invention is a method that allows a group of independent participants to coordinate decisions with respect to the allocation of interdependent resources, while maintaining certain privacy guarantees. The present invention proposes ...

2009

E[DPOP]: Distributed Constraint Optimization under Stochastic Uncertainty using Collaborative Sampling

Boi Faltings, Thomas Léauté

Many applications that require distributed optimization also include uncertainty about the problem and the optimization criteria themselves. However, current approaches to distributed optimization assume that the problem is entirely known before optimizati ...

2009

FRODO 2.0: An Open-Source Framework for Distributed Constraint Optimization

Thomas Léauté, Brammert Ottens, Radoslaw Szymanek

Distributed Constraint Optimization (DCOP) is a field that has recently been getting more and more attention from academia and industry. However, very few open-source, off-the-shelf tools are currently available to solve DCOPs; examples are FRODO, DisChoco ...

2009

Privacy-Preserving Multi-agent Constraint Satisfaction

Boi Faltings, Thomas Léauté

Constraint satisfaction has been a very successful paradigm for solving problems such as resource allocation and planning. Many of these problems pose themselves in a context involving multiple agents, and protecting privacy of information among them is of ...

IEEE Computer Society Press2009

Method to allocate inter-dependent resources by a set of participants

Boi Faltings, Adrian Petcu, Thomas Léauté

The object of the present invention is a method that allows a group of independent participants to coordinate decisions with respect to the allocation of interdependent resources, while maintaining certain privacy guarantees. The present invention proposes ...

2009

Privacy Guarantees through Distributed Constraint Satisfaction

Boi Faltings, Adrian Petcu, Thomas Léauté

The reason for using distributed constraint satisfaction algorithms is often to allow agents to find a solution while revealing as little as possible about their variables and constraints. So far, most algorithms for DisCSP do not guarantee privacy of this ...

2008