Paris Dauphine University

About: Paris Dauphine University is a education organization based out in Paris, France. It is known for research contribution in the topics: Context (language use) & Population. The organization has 1766 authors who have published 6909 publications receiving 162747 citations. The organization is also known as: Paris Dauphine & Dauphine.

On the Communication Complexity of Multilateral Trading: Extended Report

Abstract: We study the complexity of a multilateral negotiation framework, where autonomous agents agree on a sequence of deals to exchange sets of discrete resources in order to both further their own goals and to achieve a distribution of resources that is socially optimal. When analysing such a framework, we can distinguish different aspects of complexity: How many deals are required to reach an optimal allocation of resources? How many communicative exchanges are required to agree on one such deal? How complex a communication language do we require? And finally, how complex is the reasoning task faced by each agent?

Le marché selon la sociologie économique

Abstract: Depuis le milieu des annees soixante-dix, la « New Economic Sociology » a ete amenee a considerer de pres le fonctionnement des marches, domaine jusqu’alors quasiment reserve a la discipline economique car, malgre l’importance de ce fait social (Orlean 2005), les sociologues ne se sentaient pas une legitimite suffisante pour intervenir sur ce domaine. A cote de la dynamique propre aux Etats-Unis (Guillen 2002 ; Swedberg 2003), il existe aussi en Europe un interet marque pour l’approche sociol...

Algorithm and knowledge engineering for the TSPTW problem

Abstract: The well-known traveling salesman problem (TSP) is concerned with determining the shortest route for a vehicle while visiting a set of cities exactly once. We consider knowledge and algorithm engineering in combinatorial optimization for improved solving of complex TSPs with Time Windows (TSPTW). To speed-up the exploration of the applied Nested Monte-Carlo Search with Policy Adaption, we perform beam search for an improved compromise of search breadth and depth as well as automated knowledge elicitation to seed the distribution for the exploration. To evaluate our approach, we use established TSPTW benchmarks with promising results. Furthermore, we indicate improvements for real-world logistics by its use in a multiagent system. Thereby, each agent computes individual TSPTW solutions and starts negotiation processes on this basis.