Dynamics of collective behaviour in large scale self-organizing systems
Contact person:
Not specified
| Most animals usually do not live as solitary creatures. Instead they organize into social groups of sometimes large numbers, then often called a herd or a swarm. In the process of doing so each individual (“EGO”) will experience all others (“ALTER”) as being part of its own environment. A general principle for improved survival is predictive learning, which is learning to predict the near-future development of EGO’s environment. Animals/agents that have such a learning mechanism available will necessarily also try to learn predicting the behaviour of all ALTERs, creating a system where the agents will not only mutually influence each others behaviour but also each others learning. |
| The goal of this project group is three-fold: |
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| Movies: |
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| Self-organized clustering of 150 robots . Each individual can sense solely the direction of its closest neighbor. (divx codec required) | Obstacle avoidance behavior acquisition with the ICO learning rule by 15 interacting robots. | Clustering in a "learning" gas with 4096 particels. |
Main cooperation partners:
- Frank Pasemann (Fraunhofer IAIS),
- Holger Schanz, Fred Wolf (MPI Dynamics and Self-Organization)
Belongs to Group(s):
Computational Neuroscience