Vincent Chevrier

Probing robustness of cellular automata through variations of asynchronous updating

Typically viewed as a deterministic model of spatial computing, cellular automata are here considered as a collective system subject to the noise inherent to natural computing. The classical updating scheme is replaced by stochastic versions which either randomly update cells or disrupt the cell-to-cell transmission of information. We then use the novel updating schemes to probe the behaviour of elementary cellular automata, and observe a wide variety of results. We study these behaviours in the scope of macroscopic statistical phenomena and microscopic analysis. Finally, we discuss the possibility to use updating schemes to probe the robustness of complex systems.

A Reactive Approach for Solving Constraint Satisfaction Problems

We propose in this paper a multi-agent model for solving a class of Constraint Satisfaction Problems: the assignment problem. Our work is based on a real-world problem, the assignment of land-use categories in a farming territory, in the north-east of France. This problem exhibits a function to optimize, while respecting a set of constraints, both local (compatibility of grounds and land-use categories) and global (ratio of production between land-use categories). We developed amodel using a purely reactivemulti-agent systemthat builds its solution upon conflicts that arise during the resolution process. In this paper, we present the reactive modelling of the problem solving and experimental results from two points of view: the efficiency of the problem being solved and the properties of the problem solving process.

Multi-agent Multi-Model Simulation of Smart Grids in the MS4SG Project

This paper illustrates how the multi-agent approach, or paradigm, can help in the modeling and the simulation of smart grids in the context of MS4SG (a joint project between LORIA-INRIA and EDF RD for example modeling tools of the power grids, of telecommunication networks, and of the information and decision systems. This paper describes the use of MECSYCO as a valid approach to integrate these heterogeneous models in a multi-agent smart grid simulation platform. Several use cases show the ability of MECSYCO to effectively take into account the requirements of smart grids simulation in MS4SG.

How social spiders inspired an approach To region detection

Reactive problem solving is a way to propose systems composed of simple interacting agents that collectively solve problems outside the scope of individual perceptions. In this domain, natural social systems are sources of inspiration for simple mechanisms.This article presents an approach to region detection inspired by social spiders. Based on a behavioral model determined by the simulation of collective weaving, we describe how we transposed it to obtain an approach for region detection in gray level images and we propose a first assessment of the approach.

Agents & artefacts for multiple models coordination: objective and decentralized coordination of simulators

Complex systems simulation implies the interaction of different scientific fields. However, most of the time people involved into the simulation process do not know intricate distributed simulation tools and only care about their own domain modelling. We propose a framework (called AA4MM) to build a simulation as a society of interacting models. The main goal is to reuse existing models and simulators and to make them interact. The coordination challenges remain to the AA4MM framework so that the simulation design and implementation stay as simple as possible. In this paper, we present the coordination model which intends to decentralize the simulators interactions. We propose to use the environment through the notion of artefact in order to deal with the coherence, compatibility and coordination issues that appear in parallel simulations.

First Steps on Asynchronous Lattice-Gas Models with an Application to a Swarming Rule

Lattice-gas cellular automata are often considered as a particular case of cellular automata in which additional constraints apply, such as conservation or spatial exclusion of particles. But what about their updating? How to deal with non-perfect synchrony? Novel definitions of asynchronism are proposed that respect the specificity of lattice-gas models. These definitions are then applied to a well-known swarming rule in order to explore the robustness of the model to perturbations of its updating.

Interac-DEC-MDP: Towards the Use of Interactions in DEC-MDP

This article presents a new formalism Interac-DEC-MDP whose aim is to introduce the concept of interaction in Decentralized Markov Decision Process and which has been inspired by biology. The aim of this formalism, Interac-DEC-MDP, is to describe and represent interactions among agents. The outcome of interactions is decided collectively by two agents and is in charge of the distribution of local rewards. We have modeled a biological experiment within this formalism. A simple learning algorithm applied on this formalism generates a more efficient collective behavior than without interactions.

A Multi-Agent System for the Simulation of Land Use Organization

We built a multi-agent system for simulating land-use organization in farming territories in the north-east of France. Farming territories were described with soil, slope and distance features. Farming systems were described as sets of land-use categories which had needs and soil, slope or distance constraints. Our multi-agent system was inspired by the eco problem solving approach: each land-use categorie was represented by a set of agents which tried to conquer zones to satisfy its needs, fighting each other. Our system was shown convenient for our problem and provided valide solutions on real data sets.

First steps on asynchronous lattice-gas models with an application to a swarming rule

Lattice-gas cellular automata are often considered as a particular case of cellular automata in which additional constraints apply, such as conservation of particles or spatial exclusion. But what about their updating? How to deal with non-perfect synchrony? Novel definitions of asynchronism are proposed that respect the specific hypotheses of lattice-gas models. These definitions are then applied to a swarming rule in order to explore the robustness of the global emergent behaviour. In particular, we compare the synchronous and asynchronous case, and remark that a paradoxical phenomenon, the anti-alignment of particles, is no longer observed when a small but not infinitesimal amount of asynchronism is added.

A Robustness Approach to Study Metastable Behaviours in a Lattice-Gas Model of Swarming

Research in biology is increasingly interested in discrete dynamical systems to simulate natural phenomena with simple models. But how to take into account their robustness? We illustrate this issue by considering the behaviour of a lattice-gas model with an alignment-favouring interaction rule. This model, which has been shown to display a phase transition between an ordered and a disordered phase, follows ergodic dynamics. We present a method based on the study of stability and robustness, and show that the organised phase may result in several different behaviours. We then observe that behaviours are influenced asymptotically by the definition of the cellular lattice.