Tables, Memorized Semirings and Applications

We define and construct a new data structure, the tables, this structure generalizes the (finite) $k$-sets sets of Eilenberg \cite{Ei}, it is versatile (one can vary the letters, the words and the coefficients). We derive from this structure a new semiring (with several semiring structures) which can be applied to the needs of automatic processing multi-agents behaviour problems. The purpose of this account/paper is to present also the basic elements of this new structures from a combinatorial point of view. These structures present a bunch of properties. They will be endowed with several laws namely : Sum, Hadamard product, Cauchy product, Fuzzy operations (min, max, complemented product) Two groups of applications are presented. The first group is linked to the process of "forgetting" information in the tables. The second, linked to multi-agent systems, is announced by showing a methodology to manage emergent organization from individual behaviour models

Different goals in multiscale simulations and how to reach them

In this paper we sum up our works on multiscale programs, mainly simulations. We first start with describing what multiscaling is about, how it helps perceiving signal from a background noise in a ?ow of data for example, for a direct perception by a user or for a further use by another program. We then give three examples of multiscale techniques we used in the past, maintaining a summary, using an environmental marker introducing an history in the data and finally using a knowledge on the behavior of the different scales to really handle them at the same time

Automata-based Adaptive Behavior for Economical Modelling Using Game Theory

In this chapter, we deal with some specific domains of applications to game theory. This is one of the major class of models in the new approaches of modelling in the economic domain. For that, we use genetic automata which allow to build adaptive strategies for the players. We explain how the automata-based formalism proposed - matrix representation of automata with multiplicities - allows to define semi-distance between the strategy behaviors. With that tools, we are able to generate an automatic processus to compute emergent systems of entities whose behaviors are represented by these genetic automata

Moderate Growth Time Series for Dynamic Combinatorics Modelisation

Here, we present a family of time series with a simple growth constraint. This family can be the basis of a model to apply to emerging computation in business and micro-economy where global functions can be expressed from local rules. We explicit a double statistics on these series which allows to establish a one-to-one correspondence between three other ballot-like strunctures

Changing Levels of Description in a Fluid Flow Simulation

We describe here our perception of complex systems, of how we feel the different layers of description are important part of a correct complex system simulation. We describe a rough models categorization between rules based and law based, of how these categories handled the levels of descriptions or scales. We then describe our fluid flow simulation, which combines different fineness of grain in a mixed approach of these categories. This simulation is built keeping in mind an ulterior use inside a more general aquatic ecosystem

Agent-Based Perception of an Environment in an Emergency Situation

We are interested in the problem of multiagent systems development for risk detecting and emergency response in an uncertain and partially perceived environment. The evaluation of the current situation passes by three stages inside the multiagent system. In a first time, the situation is represented in a dynamic way. The second step, consists to characterise the situation and finally, it is compared with other similar known situations. In this paper, we present an information modelling of an observed environment, that we have applied on the RoboCupRescue Simulation System. Information coming from the environment are formatted according to a taxonomy and using semantic features. The latter are defined thanks to a fine ontology of the domain and are managed by factual agents that aim to represent dynamically the current situation