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.
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 language | English |
|---|---|
| Title of host publication | Advances in Artificial Life, ECAL 2011 |
| Subtitle of host publication | Proceedings of the Eleventh European Conference on the Synthesis and Simulation of Living Systems |
| Editors | Tom Lenaerts, Mario Giacobini, Hugues Bersini, Paul Bourgine, Marco Dorigo, René Doursat |
| Place of Publication | Paris, France |
| Publisher | MIT Press |
| Pages | 688-696 |
| Number of pages | 9 |
| ISBN (Electronic) | 0-262-29714-0, 978-0-262-29714-1 |
| Publication status | Published - 2011 |