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Parameters adaptation into reactive multi-agents systems: application in mobile robotics
Domain
Artificial Intelligence
Context
Researsh's works in school period
Period
February 2004   -   June 2004
State
Finished
Language(s)
Java
Link(s)
Report  -  Support  -  Open source project

Description
I performed this work during a training period of Postgraduate Degree in Computer Science (research) with the MAIA team, supervised by Vincent Chevrier.

Subject: (It's recommended to read the Scientific context before.)

   The aim of the work initially consisted in studying various methods suggested in the literature to answer the problem of the parameters' tuning.
Then, we awaited a specific proposal to develop the model within the team, our ambition was to allow an easy adaptation of parameters when experimenting conditions changes, with a continuous adaptation accorded to the system's evolution.

   My research lead me into analyzing various related research works in order to observe the potential existence of similar problems within different contexts. Thus, the use of an optimization method seemed relevant to achieve our goals; it's why by defining a protocol of resolution implementing - amongst other things - such a method, the instantiation we made, was designed to function with the works of Franck Gechter, as well using the descent of gradient defined by Laurent Jeanpierre. The results obtained offered interesting brief replies.

My report of Postgraduate Degree in Computer Science (research) (in french), as well as my support presentation (in french) are at your disposal. They offers a good global vision of the whole of my work.

Remark(s)    
   Thanks to messages' exchanges between various modules of software architecture, I was able to realize the Parameters Tuning Unity (PTU) which initially adapted those of the reactive multi-agents system conceived and implemented by Franck Gechter.
In order to make evolve the Parameters Tuning Unity and widen the range of systems being able to profit from it, while allowing the interested people to take part in its evolution, I created a dedicated project Open source. You can find information concerning the Parameters Tuning Unity, on the project's site hosted by Source Forge.

If you wish to test the Parameters Tuning Unity with the system created by Franck Gechter, you must contact him to obtain its source code.

Installation
   To use the Parameters Tuning Unity, it is enough for you to have version 1.2 (or later) of the JRE (work was carried out with version 1.4).



Scientific context
   A reactive multi-agent system is a system characterized on the level of the agents by forms of behaviors and by simple interactions which allow the observation of complex collective ownerships. Such systems have several assets: simplicity, robustness, adaptivity, reactivity and flexibility. Thus offering an attractive prospect for the collective resolution of problems.

   Nevertheless, these systems still actually suffer of an important disadvantage: their construction and their exploitation in a particular application require to tune the parameters of the subjacent model by experiments for it to show, with honourable performances, the necessary properties.

   In the MAIA team, it has been proposed a reactive model of behavior and interaction based on the physical principle of attraction and repulsion forces. The team has applied this original model successfully to a task of localization in mobile robotics.

   This model and its application to the localization provides attractive results and shows that we can resolve collectively this complex problem with very simple individual behaviour.
Nevertheless, there are still some issues when it is necessary to adapt the model's parameters with (quasi-) automatic methods when the experimenting conditions changes. For example, speed of the moving targets, type of trajectory, etc.


References
Van Parunak, H. and  Brueckner, S. : "Entropy and Self-Organization in Multi-Agent Systems", International Conference on Autonomous Agents, 2001.

Van Parunak, H. : "'Go to the Ant': Engineering Principles from Natural Agent Systems", Annals of Operations Research 75:69-101, 1997.

Bonabeau, E. and  Dorigo, M. and  Theraulaz, G. : "Swarm Intelligence", Oxford University Press, 1999.

Gechter, Franck : "Modèle multi-agents réactifs pour la fusion de percepts, application à la localisation et au suivi en robotique mobile", thesis of UHP NANCY I, 2003.

Jeanpierre, Laurent : "Apprentissage et adaptation pour la modélisation stochastique de systèmes dynamiques rééls", thesis of UHP NANCY I, 2002.
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