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Research results
Ph.D de

Ph.D
Group : Learning and Optimization

Robust Preference-based Reinforcement Learning

Starts on 08/11/2010
Advisor : SEBAG, Michèle
[SCHOENAUER Marc]

Funding :
Affiliation : Université Paris-Sud
Laboratory : LRI-AO

Defended on 30/09/2014, committee :
Directrice de thèse :
- Michele Sebag, Cnrs, Univ Paris-Sud (TAO)

Co-encadrant :
- Marc Schoenauer, Inria, Univ Paris-Sud (TAO)

Rapporteurs:
- Joelle Pineau, Univ. McGill, Canada
- Johannes Furnkranz, Univ. Darmstadt, Germany

Examinateurs :
- Michel Beaudouin-Lafon, LRI, Univ. Paris-Sud
- Pierre-Yves Oudeyer, Inria Bordeaux Sud-Ouest (Flowers)
- Paolo Viappiani, Cnrs, Univ. Paris 6

Research activities :

Abstract :


Ph.D. dissertations & Faculty habilitations
DECODING THE PLATFORM SOCIETY: ORGANIZATIONS, MARKETS AND NETWORKS IN THE DIGITAL ECONOMY
The original manuscript conceptualizes the recent rise of digital platforms along three main dimensions: their nature of coordination devices fueled by data, the ensuing transformations of labor, and the accompanying promises of societal innovation. The overall ambition is to unpack the coordination role of the platform and where it stands in the horizon of the classical firm – market duality. It is also to precisely understand how it uses data to do so, where it drives labor, and how it accommodates socially innovative projects. I extend this analysis to show continuity between today’s society dominated by platforms and the “organizational society”, claiming that platforms are organized structures that distribute resources, produce asymmetries of wealth and power, and push social innovation to the periphery of the system. I discuss the policy implications of these tendencies and propose avenues for follow-up research.

DISTRIBUTED COMPUTING WITH LIMITED RESOURCES


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