Offers “CEA”

Expires soon CEA

ROBUST MULTI-AGENT SYSTEMS BASED AND DISTRIBUTED DATA STREAM LEARNING IN A COLLABORATIVE ENV H/F (Systèmes d'information)

  • Internship
  • Gif-sur-Yvette (Essonne)
  • IT development

Job description

Domaine : Systèmes d'information

Contrat : Stage

Description du poste :

Context of this internship:
Nowadays, data streams are present in more and more applications and domains where dynamism and speed truly matters. In practice those streams represent dynamic data flows, coming from different sources, where their content evolves in time. Research has been done in the subject and many techniques for stream mining have emerged [5]. These algorithms usually sample the data stream in a certain way and deal with them incrementally or online. Despite the results provided by these new techniques, the flow of data is underutilized, which potentially leads to a loss of useful information on the one hand, and to forget what has been previously discovered on the other. Moreover the complexity of current digital applications, and those of the near future, is constantly increasing due to a combination of aspects such as the large number of sources, the non-linearity of certain processes, the distribution of knowledge and control, the time response, the strong dynamics of its environment.

Objectives of this internship:
The aim of this internship is to use agents in data streams to deal with the previously mentioned challenges. Four main blocks are potentially identified: (i) manage non synchronised data streams from different sources, (ii) do research in distributed on-line learning algorithms, (iii) increase the robustness of online learning models that deal with such streams (make them reliable through unexpected environment changes) and (iv) generate new metrics to evaluate the needs mentioned before. This work will rely and improve the STREAMER framework already existing in the lab. STREAMER is a cutting-edge data stream processing (Complex Event Processing) platform devoted to analyzing sequential data for electrical or industrial systems. Such ongoing platform already counts with independent modules which provide their own functionality, such as a graphical interface, machine learning algorithms, communication utilities, etc.
This internship may be potentially extended to a 3 years PhD.


• Engineering diploma/master 2 studies, preferable in computer science.
• Strong programming skills (Java, R, Python).
• English proficiency speaking.
• French and/or spanish is a plus.
• Knowledge in machine learning is a plus.
• Knowledge in multi-agent systems is a plus.

Ville : CEA Saclay. Gif Sur Yvette

Langue / Niveau :

Anglais : Courant

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