Inference of interaction rules of animals moving in groups usually relies on an analysis of large scale system behaviour. Models are tuned through repeated simulation until they match the observed behaviour. More recent work has used the fine scale motions of animals to validate and fit the rules of interaction of animals in groups. Here, we use a Bayesian methodology to compare a variety of mo...

This study takes place in the context of multi-agent systems (MAS), and especially reactive ones. In such a system, interactions are essential, and trigger a collective behaviour that is not directly linked to the individual ones. Whereas the evolution of the system is unknown if not tried, the regularity of emergent structures in the system is observable and forms a global behaviour. In this p...

The scope of this paper is to outline the intellectual framework, and the are of recent and forthcoming research of a doctoral project on the relation of human emotions with urban behaviour. The study of the role of emotions in the city, targets how the environment evokes emotions and behaviour, but also how human emotions influence urban phenomena in return. The elaboration of a method for the...

We describe simple simulation models of collective swarm behaviour of simple robots. We have experimented with mixed avoidance and seeking behaviour using triwheeled robots using simple ultrasonic proximity sensors. Our model assumes a radial distance of attraction or repulsion and supports multiple species in the swarm based on sensor recognition protocols. We describe the surprising success o...

study of collective actions is related to some of the most important issues in contemporary sociology such as cooperation, collective decision making, emergence of social norms etc. this paper in four steps presents a framework for studying collective actions. these steps are related to characteristics of collective actions (cooperation and common good), factors effecting the emergence of colle...

In this paper we compare the evolution of simple behaviour patterns for both an individual and a group of simulated physical robots. An evolutionary algorithm with quite general objective function is used to study the ability to develop behaviour patterns such as the maze exploring ability. The group experiments demonstrate the development of collective behaviour where the group members follow ...

Associations in mixed-species foraging groups are common in animals, yet have rarely been explored in the context of collective behaviour. Despite many investigations into the social and ecological conditions under which individuals should form groups, we still know little about the specific behavioural rules that individuals adopt in these contexts, or whether these can be generalized to heter...

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Decision-making theories explain animal behaviour, including human behaviour, as a response to estimations about the environment. In the case of collective behaviour, they have given quantitative predictions of how animals follow the majority option. However, they have so far failed to explain that in some species and contexts social cohesion increases when conditions become more adverse (i.e. ...

Slime moulds are well studied organisms in biology. They are some of the simplest organisms that exhibit complex emergent behaviour. Although individual organisms interact with the environment only by following local rules, slime moulds produce a collective behaviour on a global scale. The modelling of slime mould patterns provides a good testbed for studying emergent behaviour. We have simulat...