Skip to main content

Using a Graph Based Database to Support Collaborative Interactive Evolutionary Systems

  • Chapter
  • First Online:
Recent Advances on Hybrid Approaches for Designing Intelligent Systems

Part of the book series: Studies in Computational Intelligence ((SCI,volume 547))

  • 1379 Accesses

Abstract

Web based, collaborative, interactive evolutionary computational systems, can generate a high amount of information. There is information regarding users and their collaborations, the interaction and subjective evaluation of individuals of the population. There is also information about the actual evolutionary process: relationships between individuals and evolutionary operators, used. In this work we propose the use of graph-based databases as back end storage of the evolutionary process of collaborative interactive evolutionary systems due to the expressiveness and flexibility provided by the model and how relationships found on the system can be easily mapped to graphs. The flexibility provided enables the design of user models, social network modules that can enhance the system. As a proof of concept, a comparative implementation against a relational database is presented.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Takagi, H.: Interactive evolutionary computation: Fusion of the capacities of EC optimization and human evaluation. Proc. IEEE 89(9), 1275–1296 (2001)

    Article  Google Scholar 

  2. Secretan, J., Beato, N., D’Ambrosio, D.B., Rodriguez, A., Campbell, A., Stanley, K.O.: School of electrical engineering and computer science university of central Florida, Orlando, FL 32816-2362 {jsecreta,nbeato, ddambro, adeleinr, acampbel,kstanley}@eecs.ucf.edu Picbreeder: Evolving pictures collaboratively online

    Google Scholar 

  3. Secretan, J., Beato, N., D’Ambrosio, D.B., Rodriguez, A., Campbell, A., Folsom-Kovarik, J.T., Stanley, K.O.: Picbreeder: A case study in collaborative evolutionary exploration of design space. Evol. Comput. 19(3), 373–403 (2011)

    Article  Google Scholar 

  4. Garcia, M., Trujillo, L., Fernández-de-Vega, F., Merelo-Guervós, J.J., Olague, G.: EvoSpace-interactive: A framework to develop distributed collaborative-interactive evolutionary algorithms for artistic design. In: Proceedings of the 2nd International Conference on Evolutionary and Biologically Inspired Music, Sound, Art and Design, EvoMUSART (2013)

    Google Scholar 

  5. García-Valdez, M., Trujillo, L., de Vega, F.F., Guervós, J.J.M., Olague, G.: EvoSpace: A distributed evolutionary platform based on the tuple space model. In: Proceedings of the 16th European Conference, EvoApplications 2013, pp. 499–508. Vienna, Austria, 3–5 Apr 2013

    Google Scholar 

  6. Clune, J., Lipson, H.: Evolving three-dimensional objects with a generative encoding inspired by developmental biology. In: Proceedings of the European Conference on Artificial Life (2011)

    Google Scholar 

  7. Redis. http://redis.io/ (2013)

  8. Neo4j. http://www.neo4j.org/ (2013)

  9. Biggs, N., Lloyd, E., Wilson, R.: Graph Theory, 1736–1936. Oxford University Press, Oxford (1986)

    MATH  Google Scholar 

  10. Marko, A.: Rodriguez and neubauer, Peter the graph traversal pattern. Graph data management: Techniques and applications (2011)

    Google Scholar 

  11. Robinson, I., Webber, J., Eifrém, E.: Graph databases. O’Reilly media (2013)

    Google Scholar 

  12. Hidalgo, D., Castillo, O., Melin, P.: Type-1 and type-2 fuzzy inference systems as integration methods in modular neural networks for multimodal biometry and its optimization with genetic algorithms. Inf. Sci. 179(13), 2123–2145 (2009)

    Article  Google Scholar 

  13. Leal-Ramirez, C., Castillo, O., Melin, P., Rodriguez-Diaz, A.: Simulation of the bird age-structured population growth based on an interval type-2 fuzzy cellular structure. Inf. Sci. 181, 519–535 (2011)

    Article  MathSciNet  Google Scholar 

  14. Castillo, O., Huesca, G., Valdez, F.: Evolutionary computing for topology optimization of type-2 fuzzy controllers. Stud. Fuzziness Soft Comput. 208, 163–178 (2008)

    Article  Google Scholar 

  15. Mendoza, O., Melin, P., Castillo, O.: Interval type-2 fuzzy logic and modular neural networks for face recognition applications. Appl. Soft Comput. J. 9, 1377–1387 (2009)

    Article  Google Scholar 

  16. Mendoza, O., Melin, P., Licea, G.: Interval type-2 fuzzy logic for edges detection in digital images. Int. J. Intell. Syst. 24, 1115–1133 (2009)

    Article  MATH  Google Scholar 

  17. Valdez, F., Melin, P., Castillo, O.: Evolutionary method combining particle swarm optimization and genetic algorithms using fuzzy logic for decision making. In: Proceedings of the IEEE International Conference on Fuzzy Systems, pp. 2114–2119 (2009)

    Google Scholar 

  18. Castillo, O., Melin, P.: A review on the design and optimization of interval type-2 fuzzy controllers. Appl. Soft Comput. 12(4), 1267–1278 (2012)

    Article  Google Scholar 

  19. Cervantes, L., Castillo, O., Melin, P.: Intelligent control of nonlinear dynamic plants using a hierarchical modular approach and type-1 fuzzy logic. MICAI, pp. 1–12 (2011)

    Google Scholar 

  20. Sombra, A., Valdez, F., Melin, P., Castillo, O.: A new gravitational search algorithm using fuzzy logic to parameter adaptation. In: IEEE Congress on Evolutionary Computation, pp. 1068–1074 (2013)

    Google Scholar 

  21. Valdez, F., Melin, P., Castillo, O.: Parallel particle swarm optimization with parameters adaptation using fuzzy logic. MICAI 2, 374–385 (2012)

    Google Scholar 

  22. Valdez, F., Melin, P., Castillo, O.: Bio-inspired optimization methods on graphic processing unit for minimization of complex mathematical functions. In: Recent Advances on Hybrid Intelligent Systems, pp. 313–322 (2013)

    Google Scholar 

  23. Melendez, A., Castillo, O.: Optimization of type-2 fuzzy reactive controllers for an autonomous mobile robot. NaBIC 2012, pp. 207-211

    Google Scholar 

  24. Castillo, O., Melin, P.: Optimization of type-2 fuzzy systems based on bio-inspired methods: A concise review. Inf. Sci. 205, 1–19 (2012)

    MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to M. GarcĂ­a-Valdez .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this chapter

Cite this chapter

Romero, J.C., GarcĂ­a-Valdez, M. (2014). Using a Graph Based Database to Support Collaborative Interactive Evolutionary Systems. In: Castillo, O., Melin, P., Pedrycz, W., Kacprzyk, J. (eds) Recent Advances on Hybrid Approaches for Designing Intelligent Systems. Studies in Computational Intelligence, vol 547. Springer, Cham. https://doi.org/10.1007/978-3-319-05170-3_41

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-05170-3_41

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-05169-7

  • Online ISBN: 978-3-319-05170-3

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics