Monday, April 13, 2015

[beasiswa] [info] PhD Thesis in Multi-Agent Systems and Optimisation

 

We offer a fully-funded 3 year PhD position entitled "Multi-agent  coordination using distributed optimization based on  belief-propagation and dual decomposition - application to dynamic  prosumption".          Description  â"?â"?â"?â"?â"?â"?â"?â"?â"?â"?â"?      The information and communications technology (ICT) infrastructure is  evolving and becoming increasingly dynamic and distributed.  Considering the context of sensor networks, the internet of things or  smart power grids, the expected impact on our society is huge. The  general problem of dynamic resource allocation (data, energy, etc.)  between producers and consumers (or prosumers for those that do both)  becomes critical for these infrastructures.      Multi-agent optimization techniques are a natural fit for such  systems:      1) the optimization problem is distributed by nature,  2) the system is highly dynamic with many events emanating from both     the infrastructure and agent/human activities (and they may switch       frequently from producer to consumer, and vice versa),  3) the scale of the system calls for strong privacy, which cannot be     provided by a centralized system.      In the past years, multi-agent systems have been developed by using  message passing algorithms inspired by statistical machine learning  methods. Belief propagation is for instance designed for MAP (maximum  a posteriori) inference in probabilistic graphical models. Its  efficiency (in time and number of iterations) made it possible to  solve, in real time, problems like optimal energy allocation and  automatic service composition in sensor networks. Other message  passing algorithms using dual decomposition of the problem have  similar characteristics.      However, these approaches have some limitations â?"e.g. optimality and  convergence on cyclic networks. Despite recent advances, message  passing is still challenging and remains an open problem. Moreover,  since we consider problems with high dynamics and time-dependencies  (e.g. due to the flexible structure of the network, due to real-time  updates coming from sensors), extending such techniques seems  promising thanks to their runtime efficiency which can be exploited to  handle dynamics (though repeated solving processus) and  time-dependencies (by adding new time-related dimensions and  constraints).      This thesis subject aims at producing new methods and algorithms for  distributed optimization in dynamic networks with cycles.  It will  involve the following steps, non-exhaustively:      1. formalizing the problem of dynamic resource allocation and doing a     theoretical analysis of the existing algorithms,  2. proposing new algorithms to handle the cyclic and dynamic nature of     the networks,  3. implementing these algorithms in the form of generalization and     extensions of existing algorithms,  4. evaluating empirically the algorithms by applying them to real data     coming from the SEAS project, and deploying it into a smart-objects     platform at EMSE.          General Information  â"?â"?â"?â"?â"?â"?â"?â"?â"?â"?â"?â"?â"?â"?â"?â"?â"?â"?â"?      Duration: 3 years      Location: Saint-Etienne, France, with a possible collaboration with  IIIA-CSIC in Barcelona (Spain)      Supervisors: Gauthier Picard (MINES Saint-Etienne, Laboratoire Hubert  Curien UMR CNRS 5516, [http://www.emse.fr/~picard/]), Rémi Emonet  (Université Jean Monnet, Laboratoire Hubert Curien UMR CNRS 5516,  [http://home.heeere.com/])      Collaboration: Juan Antonio Rodriguez-Aguilar (IIIA-CSIC,  [http://www.iiia.csic.es/~jar/]), Jesus Cerquides (IIIA-CSIC)          Agenda  â.Oâ.Oâ.Oâ.Oâ.Oâ.O      Application deadline: May 10th      Interviews: May 15th to 20th      Final decision: first half of June      Starting date: September/October 2015          Skills related to the subject  â.Oâ.Oâ.Oâ.Oâ.Oâ.Oâ.Oâ.Oâ.Oâ.Oâ.Oâ.Oâ.Oâ.Oâ.Oâ.Oâ.Oâ.Oâ.Oâ.Oâ.Oâ.Oâ.Oâ.Oâ.Oâ.Oâ.Oâ.Oâ.O      The successful candidate will have and be willing to develop the  following skills:      â?¢ machine learning (graphical models, belief propagation, message    passing algorithms),  â?¢ multi-agent systems, distributed optimization,  â?¢ proficiency in programming (Java/Python, C for Arduino) and    optimization software (CPLEX, Gurobi),  â?¢ autonomy and English proficiency.          Location  â.Oâ.Oâ.Oâ.Oâ.Oâ.Oâ.Oâ.O      Saint-Etienne is located about 2 hours from the mediterranean sea and  2 hours from Alps slopes. Lyon city is at 50 km. Saint Etienne has  about 180.000 inhabitants including more than 20.000 students.  Surrounded by hills where hiking and mountain biking are significant,  Saint Etienne is also member of the Unesco Creative Cities Network for  design.  [http://en.wikipedia.org/wiki/Saint-Ã?tienne]          Contact and application  â.Oâ.Oâ.Oâ.Oâ.Oâ.Oâ.Oâ.Oâ.Oâ.Oâ.Oâ.Oâ.Oâ.Oâ.Oâ.Oâ.Oâ.Oâ.Oâ.Oâ.Oâ.Oâ.O      The application should include a motivation letter (short but  pertinent), a CV, degrees and grades, and relevant publications if any  (or Master thesis).  Candidates are also encouraged to provide  letter(s) of recommendation and contact information to reference  persons.      Applications must be sent before May 10th 2015, candidates are  encouraged to send application earlier.  Applications should be sent  to both of the following addresses: gauthier.picardâ?"atâ?"emse.fr AND  remi.emonetâ?"atâ?"univ-st-etienne.fr  _______________________________________________  

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