Artificial Intelligence Review

, Volume 34, Issue 3, pp 221–234

Problem solving techniques in cognitive science

  • Joan Condell
  • John Wade
  • Leo Galway
  • Michael McBride
  • Padhraig Gormley
  • Joseph Brennan
  • Thiyagesan Somasundram
Article

DOI: 10.1007/s10462-010-9171-0

Cite this article as:
Condell, J., Wade, J., Galway, L. et al. Artif Intell Rev (2010) 34: 221. doi:10.1007/s10462-010-9171-0

Abstract

For many years, researchers have tried to discover how humans solve problems. This research has answered many questions, but still many of them remain unanswered. However, knowledge gained in this field has greatly enhanced our understanding and has enabled us to design human-like intelligent systems. In the 1920s the Gestalt psychologists introduced a new field to cognitive science. They discovered that when presented with certain problems we use insight to reach a solution. In the 1950s Newell & Simon then brought the field of problem solving into the information age. They experimented with the idea of problem solving as a search for a solution in a state space. This technique is today utilized in the field of computing and Artificial Intelligence. This paper reviews techniques and looks at how we use previous experience gained by solving problems to solve new similar problems, making analogies between them. Experts’ performance during problem solving is compared to that of novices.

Keywords

Problem solvingGestalt approachAnalogiesExpertsNovices

Copyright information

© Springer Science+Business Media B.V. 2010

Authors and Affiliations

  • Joan Condell
    • 1
  • John Wade
    • 1
  • Leo Galway
    • 1
  • Michael McBride
    • 1
  • Padhraig Gormley
    • 1
  • Joseph Brennan
    • 1
  • Thiyagesan Somasundram
    • 1
  1. 1.School of Computing and Intelligent Systems, Faculty of Computing and EngineeringUniversity of Ulster at MageeLondonderryNorthern Ireland