Resource Allocation and Scheduling based on Emergent behaviours in Multi-Agent Scenarios

Hanno Hildmann, Miquel Martin

2015

Abstract

We present our observations regarding the emergent behaviour in a population of agents following a recently presented nature inspired resource allocation / scheduling method. By having agents distribute tasks among themselves based on their local view of the problem, we successfully balance the work across agents, while remaining flexible to adapt to dynamic scenarios where tasks are added, removed or modified. We explain the approach and within it the mechanisms that give rise to the emergent behaviour; we discuss the model used for the simulations, outline the algorithm and provide results illustrating the performance of the method.

References

  1. Bartholdi, J. J. and Eisenstein, D. D. (1996). A production line that balances itself. Operations Research, 44(1):21-34.
  2. Beckers, R., Holland, O., and Deneubourg, J.-L. (1994). From local actions to global tasks: stigmergy and collective robots. In Proceedings of the Workshop on Artificial Life, pages 181-189, Cambridge, MA. MIT Press.
  3. Bonabeau, E., Dorigo, M., and Theraulaz, G. (2000). Inspiration for optimization from social insect behaviour. Nature, 406:39-42.
  4. Camazine, S., Deneubourg, J.-L., Franks, N. R., Sneyd, J., Theraulaz, G., and Bonabeau, E. (2001). SelfOrganization in Biological Systems. Princeton Univ Press.
  5. Dussutour, A., Fourcassie, V., Helbing, D., and Deneubourg, J.-L. (2004). Optimal traffic organization in ants under crowded conditions. Nature, 428:70-73.
  6. Hassan, H. and Al-Hamadi, A. (2008). On comparative evaluation of Thorndike's psycho-learning experimental work versus an optimal swarm intelligent system. In Computational Intelligence for Modelling Control Automation, 2008 International Conference on, pages 1083 -1088.
  7. Hildmann, H. and Martin, M. (2014). Adaptive scheduling in dynamic environments. In 2014 Federated Conference on Computer Science and Information Systems (FedCSIS), pages 1331-1336.
  8. Holland, J. (1998). Emergence: From Chaos to Order. Helix books. Oxford University Press.
  9. Luss, H. (2012). Equitable Resource Allocation: Models, Algorithms and Applications. Information and Communication Technology Series. Wiley.
  10. Pinedo, M. (2012). Scheduling: Theory, Algorithms, and Systems. SpringerLink : Bücher. Springer.
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Paper Citation


in Harvard Style

Hildmann H. and Martin M. (2015). Resource Allocation and Scheduling based on Emergent behaviours in Multi-Agent Scenarios . In Proceedings of the International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES, ISBN 978-989-758-075-8, pages 140-147. DOI: 10.5220/0005219501400147


in Bibtex Style

@conference{icores15,
author={Hanno Hildmann and Miquel Martin},
title={Resource Allocation and Scheduling based on Emergent behaviours in Multi-Agent Scenarios},
booktitle={Proceedings of the International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES,},
year={2015},
pages={140-147},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005219501400147},
isbn={978-989-758-075-8},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES,
TI - Resource Allocation and Scheduling based on Emergent behaviours in Multi-Agent Scenarios
SN - 978-989-758-075-8
AU - Hildmann H.
AU - Martin M.
PY - 2015
SP - 140
EP - 147
DO - 10.5220/0005219501400147