situation and its evolution in time. This part is modelled with an original information representation methodology which is based on the handle **of semantic**
features using a factual agents organisation.

The model of the first layer was applied on the game of Risk. Results provided by this test correspond to our attempts, which consist on the dynamic representation of information. This application allowed us to track the behaviour of factual agents and to understand their parameters which are the most accurate to characterise information. Moreover, we consider that a great part of the system is generic and may be carried into other fields. Currently, we **intend in**
a first time to connect the representation layer to the two other and to apply thereafter the whole system on more significant domains as RoboCup Rescue and e-learning.

## References

1. Boukachour, H.: Syst´eme de veille pr´eventive pour la gestion de situations d'urgence: une mod´elisation par organisation d'agents. Application aux risques industriels. PhD Thesis, University of le Havre, France (2002)
2. Boukachour, H., Galinho, T., Person, P., Serin, F.: Towards an architecture for the representation of dynamic situations. In Las Vegas IC-AI 659-664 (2003)q 3. Cardon, A.: A multi-agent model for cooperative communications in crisis management system: the act of communication. In 7th European-Japanese Conference on Information Modeling and Knowledge-Based Simulation 111-123 (1997)
4. Cardon, A.: Mod´eliser et concevoir une machine pensante: approhce de la conscience artificielle, Vuibert, (2004)
5. Durand, S.: Repr´esentation des points de vue multiples dans une situation d'urgnece: une mod´elisation par organisation d'agents. PhD Thesis, University of Le Havre, France (1999)
6. http://www.fipa.org, last retrieved March (2006)
7. Galinho, T., Serin, F.: Semantic Features And Factual Agents: A Model To Represent Changeable Situations A Model To Rpresent Changeable Situations (2003)
8. Galinho, T., Coletta, M., Person, P., Serin, F.: Dynamic Representation of Information for a Decision Support System, 8th International **Conference on Entreprise Information, ICEIS2006, Paphos, Cyprus, (2006)**
9. Kitano, H., Tadokoro, S.: RoboCup Rescue A Grand Challenge for Multiagent and Intelligent Systems, American Association for Artificial Intelligence (2001)
10. Person, P., Boukachour, H., Coletta, M., Galinho, T., Serin, F.: From Three MultiAgent Systems to One Decision Support System, 2nd**Indian International**
Conference on Artificial Intelligence**, Pune, India (2005)**
11. http://sasemas.org/2005/challenge.html, last retrieved March (2006)
http://www.rescuesystem.org/robocuprescue, last retrieved March (2006)
12. http://www.thegamesjournal.com/articles/Risk.shtml, last retrieved March
(2006)
http://www.tuxick.net/xfrisk/doc/riskfaq.html, last retrieved March (2006)
13. Wooldridge, M., Jennings, N.R.: Pitfalls of agent-oriented development 2nd International Conference en Autonomous Agents, pp. 385-391, **Minneapolis, (1998)**
14. Wooldridge, M.: An Introduction to MultiAgent Systems, Wiley, (2002)