research-article

Description and composition of bio-inspired design patterns: the gradient case

Authors:

Jose Luis Fernandez-Marquez,

Josep Lluis Arcos,

Giovanna Di Marzo Serugendo,

Sara MontagnaAuthors Info & Claims

BADS '11: Proceedings of the 3rd workshop on Biologically inspired algorithms for distributed systems

Pages 25 - 32

https://doi.org/10.1145/1998570.1998575

Published: 14 June 2011 Publication History

Abstract

Bio-inspired mechanisms have been extensively used in the last decade for solving optimisation problems and for decentralised control of sensors, robots or nodes in P2P systems. Different attempts at describing some of these mechanisms have been proposed, some of them under the form of design patterns. However, there is not so far a clear catalogue of these mechanisms, described as patterns, showing the relations between the different patterns and identifying the precise boundaries of each mechanism. To ease engineering of artificial bio-inspired systems, this paper describes a group of bio-inspired mechanisms in terms of design patterns organised into different layers. This approach is exemplified through the description of 7 bio-inspired mechanisms: three basic ones (Spreading, Aggregation, and Evaporation), a mid-level one (Gradient) obtained by composing the basic ones, and three top-level ones (Chemotaxis, Morphogenesis, and Quorum sensing) exploiting the mid-level one.

References

[1]

O. Babaoglu, G. Canright, A. Deutsch, G. A. D. Caro, F. Ducatelle, L. M. Gambardella, N. Ganguly, M. Jelasity, R. Montemanni, A. Montresor, and T. Urnes. Design patterns from biology for distributed computing. ACM TAAS, 1:26--66, 2006.

Digital Library

[2]

J. Beal. Flexible self-healing gradients. In SAC '09: Proceedings of the 2009 ACM symposium on Applied Computing, pages 1197--1201. ACM, 2009.

Digital Library

[3]

J. Beal, J. Bachrach, D. Vickery, and M. Tobenkin. Fast self-healing gradients. In SAC '08: Proceedings of the 2008 ACM symposium on Applied computing, pages 1969--1975, New York, NY, USA, 2008. ACM.

Digital Library

[4]

H. Bojinov, A. Casal, and T. Hogg. Multiagent control of self-reconfigurable robots, 2001.

[5]

M. Britton and L. Sack. The secoas project: development of a self-organising wireless sensor network for environmental monitoring. In 2nd International Workshop on Sensor and Actor Network Protocols and Applications, Boston, 2004.

[6]

G. Chen and D. Kotz. Solar: A pervasive-computing infrastructure for context-aware mobile applications. Technical report, Department of Computer Science, Dartmouth College Hanover, NH, USA 03755, 2002.

[7]

T. De Wolf and T. Holvoet. Design patterns for decentralised coordination in self-organising emergent systems. Engineering Self-Organising Systems, 4335:28--49, Feb. 2007.

[8]

J. Deneubourg, J. Pasteels, and J. Verhaeghe. Probabilistic behaviour in ants: A strategy of errors? Journal of Theoretical Biology, 105(2):259 -- 271, 1983.

[9]

M. Dorigo. Optimization, Learning and Natural Algorithms. PhD thesis, Politecnico di Milano, 1992.

[10]

M. Dorigo and G. Di Caro. The ant colony optimization meta-heuristic. New Ideas in Optimization, pages 11--32, 1999.

Digital Library

[11]

J. L. Fernandez-Marquez and J. L. Arcos. An evaporation mechanism for dynamic and noisy multimodal optimization. In Proc. of the Conference on Genetic and evolutionary Computation (GECCO'09), pages 17--24. ACM, 2009.

Digital Library

[12]

J. L. Fernandez-Marquez and J. L. Arcos. Adapting particle swarm optimization in dynamic and noisy environments. In Proceedings of IEEE Congress on Evolutionary Computation, pages 765--772, 2010.

[13]

J. L. Fernandez-Marquez, J. L. Arcos, G. Di Marzo Serugendo, and M. Casadei. Description and composition of bio-inspired design patterns: the gossip case. In Proc. of EASE'2011, pages 87--96. IEEE Computer Society, 2011.

Digital Library

[14]

L. Gardelli, M. Viroli, and A. Omicini. Design patterns for self-organizing multiagent systems. In Proceedings of EEDAS, 2007.

[15]

M. Mamei, R. Menezes, R. Tolksdorf, and F. Zambonelli. Case studies for self-organization in computer science. J. Syst. Archit, 52:433--460, 2006.

Digital Library

[16]

M. Mamei, M. Vasirani, and F. Zambonelli. Experiments of morphogenesis in swarms of simple mobile robots. Journal of Applied Artificial Intelligence, 18:903--919, 2004.

[17]

M. Mamei and Zambonelli. Motion coordination in the quake 3 arena environment: a field-based approach. In First International Workshop on Environments for Multiagent Systems, 2003.

Digital Library

[18]

M. B. Miller and B. L. Bassler. Quorum sensing in bacteria. Annual Review of Microbiology, 55(1):165--199, 2001.

[19]

R. Nagpal. A catalog of biologically-inspired primitives for engineering self-organization. engineering self-organising systems: Nature-inspired approaches to software engineering (2003); 2977: 53--62. In Engineering Self-Organising Systems, Nature-Inspired Approaches to Software Engineering. Volume 2977 of Lecture Notes in Computer Science, pages 53--62. Springer, 2004.

[20]

H. Parunak, M. Purcell, and R. Connell. Digital pheromones for auton. coordination of swarming uavs.

[21]

M. C. Radhika and R. Nagpal. Programmable self-assembly using biologically-inspired. pages 418--425. Press, 2002.

[22]

R. M. Ruairí and M. T. Keane. An energy-efficient, multi-agent sensor network for detecting diffuse events. In IJCAI'07: Proceedings of the 20th international joint conference on Artifical intelligence, pages 1390--1395, San Francisco, CA, USA, 2007. Morgan Kaufmann Publishers Inc.

Digital Library

[23]

E. Sahin and N. R. Franks. Measurement of space: From ants to robots. In Proceedings of WGW 2002: EPSRC/BBSRC International Workshop Biologically-Inspired Robotics, 2002.

[24]

J. Sudeikat and W. Renz. Toward systemic mas development: Enforcing decentralized self-organization by composition and refinement of archetype dynamics. In Proceedings of Engineering Environment-Mediated Multiagent Systems. Springer, 2007.

[25]

M. Viroli, M. Casadei, S. Montagna, and F. Zambonelli. Spatial coordination of pervasive services through chemical-inspired tuple spaces. ACM Transac. on Autonomous and Adapt. Systems, 2011.

Digital Library

[26]

D. Weyns, T. Holvoet, and A. Helleboogh. Anticipatory vehicle routing using delegate multi-agent systems. pages 87 --93, sep. 2007.

[27]

L. Wolpert, T. Jessell, P. Lawrence, E. Meyerowitz, E. Robertson, and J. Smith. Principles of Development. Oxford Univer. Press, 3rd edition, 2007.

Cited By

Mariani SMariani S(2016)$$\mathcal{M}\text{olecules}\,{\mathcal{o}\text{f}}\,\mathcal{K}\text{nowledge}$$ : TechnologyCoordination of Complex Sociotechnical Systems10.1007/978-3-319-47109-9_7(181-198)Online publication date: 24-Nov-2016
https://doi.org/10.1007/978-3-319-47109-9_7
Fernandez-Marquez JDi Marzo Serugendo GStevenson GYe JDobson SZambonelli FCho YShin SKim SHung CHong J(2014)Self-managing and self-organising mobile computing applicationsProceedings of the 29th Annual ACM Symposium on Applied Computing10.1145/2554850.2555042(458-465)Online publication date: 24-Mar-2014
https://dl.acm.org/doi/10.1145/2554850.2555042
Chenyu Zheng Sicker D(2013)A Survey on Biologically Inspired Algorithms for Computer NetworkingIEEE Communications Surveys & Tutorials10.1109/SURV.2013.010413.0017515:3(1160-1191)Online publication date: Nov-2014
https://doi.org/10.1109/SURV.2013.010413.00175
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Index Terms

Description and composition of bio-inspired design patterns: the gradient case
1. Computing methodologies
  1. Artificial intelligence
    1. Distributed artificial intelligence
      1. Cooperation and coordination
      2. Multi-agent systems

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Published In

cover image ACM Conferences

BADS '11: Proceedings of the 3rd workshop on Biologically inspired algorithms for distributed systems

June 2011

64 pages

ISBN:9781450307338

DOI:10.1145/1998570

General Chairs:
Gianluigi Folino
ICAR-CNR, National Research Council, Italy
,
Carlo Mastroianni
ICAR-CNR, National Research Council, Italy
,
Sanaz Mostaghim
Karlsruhe Institute of Technology, Germany
,
Junichi Suzuki
University of Massachusetts, Boston, USA

Copyright © 2011 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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IEEE
University of Arizona: University of Arizona
SIGARCH: ACM Special Interest Group on Computer Architecture

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Association for Computing Machinery

New York, NY, United States

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Published: 14 June 2011

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ICAC '11

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University of Arizona
SIGARCH

ICAC '11: 8th International Conference on Autonomic Computing

June 14, 2011

Karlsruhe, Germany

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Cited By

Mariani SMariani S(2016)$$\mathcal{M}\text{olecules}\,{\mathcal{o}\text{f}}\,\mathcal{K}\text{nowledge}$$ : TechnologyCoordination of Complex Sociotechnical Systems10.1007/978-3-319-47109-9_7(181-198)Online publication date: 24-Nov-2016
https://doi.org/10.1007/978-3-319-47109-9_7
Fernandez-Marquez JDi Marzo Serugendo GStevenson GYe JDobson SZambonelli FCho YShin SKim SHung CHong J(2014)Self-managing and self-organising mobile computing applicationsProceedings of the 29th Annual ACM Symposium on Applied Computing10.1145/2554850.2555042(458-465)Online publication date: 24-Mar-2014
https://dl.acm.org/doi/10.1145/2554850.2555042
Chenyu Zheng Sicker D(2013)A Survey on Biologically Inspired Algorithms for Computer NetworkingIEEE Communications Surveys & Tutorials10.1109/SURV.2013.010413.0017515:3(1160-1191)Online publication date: Nov-2014
https://doi.org/10.1109/SURV.2013.010413.00175
Brocco ABaumgart I(2012)A Framework for a Comprehensive Evaluation of Ant-Inspired Peer-to-Peer ProtocolsProceedings of the 2012 20th Euromicro International Conference on Parallel, Distributed and Network-based Processing10.1109/PDP.2012.53(303-310)Online publication date: 15-Feb-2012
https://dl.acm.org/doi/10.1109/PDP.2012.53
Fernandez-Marquez JSerugendo GMontagna S(2012)BIO-CORE: Bio-inspired Self-organising Mechanisms CoreBio-Inspired Models of Networks, Information, and Computing Systems10.1007/978-3-642-32711-7_5(59-72)Online publication date: 2012
https://doi.org/10.1007/978-3-642-32711-7_5
Montagna SViroli MRisoldi MPianini DDi Marzo Serugendo G(2011)Self-organising pervasive ecosystemsProceedings of the Third international conference on Software engineering for resilient systems10.5555/2045537.2045556(115-129)Online publication date: 29-Sep-2011
https://dl.acm.org/doi/10.5555/2045537.2045556
Cruz Torres MVan Beers THolvoet TLopes C(2011)(No) more design patterns for multi-agent systemsProceedings of the compilation of the co-located workshops on DSM'11, TMC'11, AGERE! 2011, AOOPES'11, NEAT'11, & VMIL'1110.1145/2095050.2095083(213-220)Online publication date: 23-Oct-2011
https://dl.acm.org/doi/10.1145/2095050.2095083
Tchao ARisoldi MDi Marzo Serugendo G(2011)Modeling Self-* Systems Using Chemically-Inspired Composable PatternsProceedings of the 2011 IEEE Fifth International Conference on Self-Adaptive and Self-Organizing Systems10.1109/SASO.2011.22(109-118)Online publication date: 3-Oct-2011
https://dl.acm.org/doi/10.1109/SASO.2011.22

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