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Experiential Solving: Towards a Unified Autonomous Search Constraint Solving Approach

  • Broderick CrawfordEmail author
  • Ricardo Soto
  • Kathleen Crawford
  • Franklin Johnson
  • Claudio León de la Barra
  • Sergio Galdames
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 528)

Abstract

To solve many problems modeled as Constraint Satisfaction Problems there are no known efficient algorithms. The specialized literature offers a variety of solvers, which have shown good performance. Nevertheless, despite the efforts of the scientific community in developing new strategies, there is no algorithm that is the best for all possible situations. This paper analyses recent developments of Autonomous Search Constraint Solving Systems. Showing that the design of the most efficient and recent solvers is very close to the Experiential Learning Cycle from organizational psychology.

Keywords

Experiential learning Problem solving Metaheuristics Autonomous search 

Notes

Acknowledgments

Broderick Crawford is supported by Grant CONICYT / FONDECYT / REGULAR / 1140897. Ricardo Soto is supported by Grant CONICYT / FONDECYT / INICIACION / 11130459.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Broderick Crawford
    • 1
    • 2
    • 3
    Email author
  • Ricardo Soto
    • 1
    • 4
    • 5
  • Kathleen Crawford
    • 1
  • Franklin Johnson
    • 1
    • 6
  • Claudio León de la Barra
    • 1
  • Sergio Galdames
    • 1
  1. 1.Pontificia Universidad Católica de ValparaísoValparaisoChile
  2. 2.Universidad Central de ChileSantiagoChile
  3. 3.Universidad San SebastiánSantiagoChile
  4. 4.Universidad Autónoma de ChileSantiagoChile
  5. 5.Universidad Cientifica del SurLimaPeru
  6. 6.Universidad de Playa AnchaValparaisoChile

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