Authors:
Guillaume Sartoretti
and
Max-Olivier Hongler
Affiliation:
École Polytechnique Fédérale de Lausanne (EPFL), Switzerland
Keyword(s):
Rank-based Brownian Motions, Heterogeneous Autonomous Agents, Soft-control of Swarms, Exact Analytic Solvable Models, Super-diffusive Shill Agent, Flocking.
Related
Ontology
Subjects/Areas/Topics:
Agents
;
Artificial Intelligence
;
Artificial Intelligence and Decision Support Systems
;
Autonomous Systems
;
Collective Intelligence
;
Distributed and Mobile Software Systems
;
Enterprise Information Systems
;
Knowledge Engineering and Ontology Development
;
Knowledge-Based Systems
;
Multi-Agent Systems
;
Self Organizing Systems
;
Software Engineering
;
Symbolic Systems
Abstract:
We analytically study the collective dynamics of mutually interacting heterogeneous agents evolving in a random environment. Our formal framework consists of a collection of N scalar drifted Brownian motions (BM) diffusing on R. The mutual interactions are introduced via a ranked-based, real-time mechanism always endowing the laggard (i.e the agent with the leftmost position) with an extra positive drift. The extra drift generates a net tendency for any agents not to remain the laggard of the society. For well chosen individual and extra laggard’s drifts, the agents organize with time to flock towards a tight and stable travelling spatial pattern. For a population of (N −1) identical agents and an atypical fellow (called hereafter the shill), we are able to analytically discuss the dynamics. In particular we exhibit how a single turbulent shill, stylized here by a ballistic diffusion process, can destroy the cohesion of a swarm. Conversely, we also analytically show how a single shil
l is able to safely pilot a whole swarm to avoid an obstacle, via interactions with its fellows. A series of simulations experiments comfort our analytic findings.
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