Seminars Organized by the LE2I


Date Hour Room Details
September 28th 14.00 Meeting Room, Building D, Belfort Dr. Fabrice Lauri
Deep Reinforcement Learning
In 2013, a small company in London called DeepMind uploaded their pioneering paper “Playing Atari with Deep Reinforcement Learning” to Arxiv. In this paper they demonstrated how a computer learned to play Atari 2600 video games by observing just the screen pixels and receiving a reward when the game score increased. The result was remarkable, because the same model architecture, without any change, was used to learn how to win in seven different games, and in three of them the algorithm performed even better than a human!

No wonder DeepMind was immediately bought by Google and has been on the forefront of deep learning research ever since. It has been hailed since then as the first step towards general artificial intelligence – an AI that can survive in a variety of environments.
The roadmap of this seminar is:
- What are the main challenges in reinforcement learning?
- How to formalize reinforcement learning in mathematical terms?
- How do we form long-term strategies?
- How can we estimate or approximate the future reward?
- What if our state space is too big? (Here the answer is simple: deep learning!)
- What are the main deep RL algorithms?
- What performances can these algorithms obtain on classical problems?
- What are the main issues of applying such algorithms?
- How to program such algorithms and validate them on common problems with Ipseity?

September 21th 14.00 Belfort Dr. Benjamin Camus
DEVS wrapping of the FMI standard for the co-simulation of Cyber-Physical Systems in MECSYCO
Most modeling and simulation (M&S) questions about cyber-physical systems (CPS) require expert skills belonging to different scientific fields. The challenges are then to integrate each domain tool (formalism and simulation software) within the rigorous framework of M&S process. To answer this issue, we proposed the specifications of the MECSYCO co-simulation middleware. MECSYCO relies on the universality of the DEVS formalism to integrate models written in different formalisms. This integration is based on a wrapping strategy in order to make models implemented with different simulation software interoperable. So far, we successfully defined DEVS wrappers for discrete modeling tools like the MAS simulator NetLogo, and the IP network simulators NS-3 and OMNeT++/INET. Aside from several difficulties met at the software level, making these discrete modeling tools compliant with the DEVS simulation protocol was a straightforward process. This is due to the fact that these platforms have a discrete modeling paradigm very close to DEVS. However, things getting more complex with equation-based tools as their continuous modeling paradigm is very different from the discrete DEVS one. Thus, we need to bridge the gap between the discrete and the continuous paradigms. A more complex wrapping strategy based on the hybrid capacity of DEVS is required. Regarding this issue, wrapping each of these equation-based tools (e.g. OpenModelica, Dymola, Matlab/Simulink) separately would be very inefficient. In this talk, I will detail how we tackle this issue by defining DEVS wrappers for the FMI standard which brings a generic API to manipulate equation-based models and their solvers. We perform this wrapping using the DEV&DESS hybrid formalism and the QSS numerical method. The DEVS wrapping of FMI we propose is not restricted to MECSYCO but can be performed in any DEVS-based platform.
June 29th 14.00 Belfort Pr. Ansar Yasar
Empowering Citizens with Sustainable Transportation in the Cities of Today & Tomorrow
While some may argue that the added value of one research domain is more limited in terms of added economic value than the other, the contribution of transportation research towards the society as a whole is significant. According to several predictions, the transport sector will overtake industry as the largest energy user by 2020. Unfortunately, the sector has major negative economic, social and environmental side effects. The complexity of today’s policy decision making has motivated several international research teams to develop policy frameworks which are finally aimed at mitigating these negative externalities of transport.

In several international policy frameworks, conventional transport models have been used for the quantification of these externalities. When an operational model is required to provide quantitative predictions about human behaviour, some kind of mathematical apparatus is adopted in models. In this talk, we will cover the research domain of activity-based models. In these models, using micro-simulation, full activity-travel patterns of people are predicted in a high resolution of time and space, offering a wealth of information for policy making. The models give us a behavioural insight at an unprecedented level and allow for many interesting interdisciplinary applications. In this talk, I will give a brief overview of the state-of-the-art in activity-based modelling and discuss the interesting developments in this field of research. In addition to applications in the domain of transportation research, I will focus on scientific interdisciplinary applications with several other scientific fields, such as emission and health impact calculations, traffic safety and future electric vehicle (market) projections. Also the talk will cover novel interesting trends in the research field such as the increasing availability of big data and the development of modern survey technology, which offers several opportunities for policy makers but also provides researchers with novel challenges and problems.

June 1th 14.00 Meeting Room, Building D, Belfort Dr. Vukosi Marivate
Machine Learning, Reinforcement Learning
June 1th 10.30 Meeting Room, Building D, Belfort Dr. Nidal Kamel
Subspace-Based Estimators for Image Denoising
Digital images are susceptible to various types of noise that may which affects their quality. In the field of image enhancement, different approaches for noise reduction have been proposed. In general, there are two basic approaches to image denoising, spatial filtering methods and transform domain filtering methods. Spatial filtering methods include linear methods like the mean and Winer and nonlinear methods, like the median and the weighted median. The performance of these filters is highly dependent on the choice of size and orientation of the moving window. Transform domain filtering methods are mostly dominated by the Wavelet, where the image is first transformed into the wavelet domain then a thresholding scheme is applied. The major drawback of the wavelet-based technique is the ringing impairments due to the thresholding process. Recently, the area of the subspace based filters, has gained widespread attention and successfully implemented in various areas of image densoing. In this lecture, two subspace-based techniques to reduce the noise in images are outlined. These techniques are the Least Squares Estimator, and the Time Domain Constraints Estimator (TDC).
May 4th 14.00 Meeting Room, Building D, Belfort Pr. Vincent Chevrier
Mecsyco: Multi-agent Environment for the Co-simulation of COmplex systems
Most modeling and simulation (M&S) questions about complex systems require to take simultaneously account of several points of view. Phenomena evolving at different scales and at different levels of resolution have to be considered. Moreover, expert skills belonging to different scientific fields are needed. The challenges are then to reconcile these heterogeneous points of view, and to integrate each domain tools (formalisms and simulation software) within the rigorous framework of the M&S process.

This talk will present the mecsyco co-simulation middleware ( Mecsyco r elies on the universality of the DEVS formalism to integrate models written in different formalism. This integration is based on a wrapping strategy in order to make models implemented in different simulation software inter-operable. The middleware performs the co-simulation in a parallel, decentralized and distributable fashion thanks to its modular multi-agent architecture.

March 16th 14.00 Meeting Room, Building D, Belfort Stéphane GALLAND
SARL - Agent-oriented Programming Language

SARL is a general-purpose agent-oriented language. It aims at providing the fundamental abstractions for dealing with concurrency, distribution, interaction, decentralization, reactivity, autonomy and dynamic reconfiguration. These high-level features are now considered as the major requirements for an easy and practical implementation of modern complex software applications, and specifically agent-oriented programming. This talk will introduce you to the advances of the SARL agent programming languages, and provides several examples of usages.



Date Hour Details
February 6th 9.30 Sebastian Rodriguez, Nicolas GAUD
SARL - Agent-oriented Programming Language


Date Hour Details
November 14th 14.00 Vincent HILAIRE
OpenModelica, un langage ad-hoc pour la simulation
September 27th 09.00-18.00 Agent Group Workshop
June 14th 10.00 Luk Knapen (IMOB, Hasselt, Belgium)
Carpooling Model.
March 10th 10.00 Olivier Boissier (EMSE, Saint-Etienne, France)
Multiagent-oriented programming


Date Hour Details
January 31th 14.30 Michael Schumacher (Applied Intelligent Systems Laboratory, Sierre, Switzerland)
Medical and Smart-grid applications at AIS Lab.


Date Hour Details
February 15th 14.00 Gildas Morvan (LGI2A Laboratory, Béthune, France)
Multilevel simulation and its applications.
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