Simulating Swarm Behaviour

The emergent collective intelligence of groups of simple agents known as swarm intelligence is a new exiting way of achieving a form of artificial intelligence. This paper studies a formal model for swarm intelligence inspired by biological swarms found in nature. Software agents are used to model the individuals of a swarm. Each agent is controlled by a neural network that processes position data from the others in its visible zone given by a compound eye and in this way navigates in 3D space. An additional input parameter is used to represent the agent’s motivation to form a swarm. Simulations with different motivation parameters exhibit remarkable agent formations that can be considered as biologically plausable. Several ways to improve the model are discussed.

W. Kramper, R. Wanker, K.-H. Zimmermann: Analysis of Swarm Behavior Using Compound Eye and Neural Network Control. J. Sig. Proc. Systems, submitted.

Simulation of Swarm Behaviour

The emergent collective intelligence of groups of simple agents known as swarm intelligence is a new exiting way of achieving a form of artificial intelligence. We are studying a formal model for swarm intelligence inspired by biological swarms found in nature. Software agents are used to model the individuals of a swarm. Each agent is controlled by a neural network that processes position data from the comrades in its visible zone given by a compound eye and in this way allows it to navigate in 3D space. An additional input parameter is used to represent the agent’s motivation to form a swarm. Simulations with different motiviation parameters exhibit remarkable agent formations that can be considered as biologically plausable. Several ways to improve the model are currently discussed.

Key Words: computational intelligence - swarm simulation - multi-agent system - neural network - compound eye.

Literature:

• W. Kramper: Simulation von Schwarmverhalten. PhD thesis, 124 p., mbv, Berlin, 2010.

Common work with Wolfgang Kramper and Ralf Wanker.