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International Conference on Hybrid Artificial Intelligence Systems

HAIS 2013: Hybrid Artificial Intelligent Systems pp 411–420Cite as

Second Order Swarm Intelligence

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Part of the Lecture Notes in Computer Science book series (LNAI,volume 8073)

Abstract

An artificial Ant Colony System (ACS) algorithm to solve general-purpose combinatorial Optimization Problems (COP) that extends previous AC models [21] by the inclusion of a negative pheromone, is here described. Several Traveling Salesman Problem (TSP) were used as benchmark. We show that by using two different sets of pheromones, a second-order coevolved compromise between positive and negative feedbacks achieves better results than single positive feedback systems. The algorithm was tested against known NP-complete combinatorial Optimization Problems, running on symmetrical TSPs. We show that the new algorithm compares favorably against these benchmarks, accordingly to recent biological findings by Robinson [26,27], and Grüter [28] where “No entry” signals and negative feedback allows a colony to quickly reallocate the majority of its foragers to superior food patches. This is the first time an extended ACS algorithm is implemented with these successful characteristics.

Keywords

  • Self-Organization
  • Stigmergy
  • Co-Evolution
  • Swarm Intelligence
  • Dynamic Optimization
  • Foraging
  • Cooperative Learning
  • Combinatorial Optimization problems
  • Symmetrical Traveling Salesman Problems (TSP)

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  • DOI: 10.1007/978-3-642-40846-5_41
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Author information

Authors and Affiliations

  1. LaSEEB – Evolutionary Systems and Biomedical Eng. Lab., ISR – Robotic and Systems Institute, Technical University of Lisbon (IST), Av. Rovisco País, 1 Torre Norte, 6.21, 1049-001, Lisbon, Portugal

    Vitorino Ramos

  2. The Open University, Milton Keynes, United Kingdom

    David M. S. Rodrigues

  3. The Observatorium - ISCTE-IUL, Lisbon University Institute (IUL), Av. Forças Armadas, 1649-026, Lisbon, Portugal

    David M. S. Rodrigues & Jorge Louçã

Authors
  1. Vitorino Ramos
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  2. David M. S. Rodrigues
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  3. Jorge Louçã
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Editor information

Editors and Affiliations

  1. Department of Electronic Engineering, National Kaohsiung University of Applied Sciences, No. 415, Chien Kung Road, 80778, Kaohsiung, Taiwan

    Jeng-Shyang Pan

  2. Department of Electrical and Computer Engineering, University of Cyprus, 75 Kallipoleos Avenue, 1678, Nicosia, Cyprus

    Marios M. Polycarpou

  3. Department of Systems and Computer Networks, Wroclaw University of Technology, Wybrzeze Wyspianskiego 27, 50-370, Wroclaw, Poland

    Michał Woźniak

  4. Department of Computer Science, University of Sao Paulo at Sao Carlos, Sao Carlos, SP, Brazil

    André C. P. L. F. de Carvalho

  5. University of Salamanca, Plaza de la Merced S/N, 37008, Salamanca, Spain

    Héctor Quintián & Emilio Corchado & 

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Ramos, V., Rodrigues, D.M.S., Louçã, J. (2013). Second Order Swarm Intelligence. In: Pan, JS., Polycarpou, M.M., Woźniak, M., de Carvalho, A.C.P.L.F., Quintián, H., Corchado, E. (eds) Hybrid Artificial Intelligent Systems. HAIS 2013. Lecture Notes in Computer Science(), vol 8073. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40846-5_41

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  • DOI: https://doi.org/10.1007/978-3-642-40846-5_41

  • Publisher Name: Springer, Berlin, Heidelberg

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