Local Information Maximisation creates Emergent Flocking Behaviour

Research output: Chapter in Book/Report/Conference proceedingConference contribution

57 Downloads (Pure)

Abstract

The three boids rules of alignment, separation and cohesion,
introduced by Reynolds to recreate flocking behaviour have
become a well known standard to create swarm behaviour. In
this paper we want to demonstrate how similar flocking behaviour
can be created by a local, agent based model, following
a principle of information maximisation. The basis for
our model is an extension of Vergassola’s infotaxis model,
where agents determine their actions based on the highest expected
reduction of entropy. We adapted this approach to a
grid world-based search task, and extended the agents abilities
so they could not only perform a Bayesian update with
information gained from the environment, but also with information
gained from other agents. The resulting global flocking
behaviour is then analysed in regard to how well it resembles
the basic boids rules.
Original languageEnglish
Title of host publicationAdvances in Artificial Life, ECAL 2011
Subtitle of host publicationProceedings of the Eleventh European Conference on the Synthesis and Simulation of Living Systems
EditorsTom Lenaerts, Mario Giacobini, Hugues Bersini, Paul Bourgine, Marco Dorigo, René Doursat
Place of PublicationParis, France
PublisherMIT Press
Pages688-696
Number of pages9
ISBN (Electronic)0-262-29714-0, 978-0-262-29714-1
Publication statusPublished - 2011

Fingerprint

Dive into the research topics of 'Local Information Maximisation creates Emergent Flocking Behaviour'. Together they form a unique fingerprint.

Cite this