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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