Simulating human heuristic problem solving: a study by combining ACT-R and fMRI brain image

  • Authors:

  • Rifeng Wang;Jie Xiang;Haiyan Zhou;Yulin Qin;Ning Zhong

  • Affiliations:

  • The International WIC Institute, Beijing University of Technology, China and Dept of Computer Science, Guangxi University of Technology, China;College of Computer and Software, Taiyuan University of Technology, China and The International WIC Institute, Beijing University of Technology, China;The International WIC Institute, Beijing University of Technology, China;The International WIC Institute, Beijing University of Technology, China and Dept of Psychology, Carnegie Mellon University;The International WIC Institute, Beijing University of Technology, China and Dept of Life Science and Informatics, Maebashi Institute of Technology, Japan

  • Venue:
  • BI'09 Proceedings of the 2009 international conference on Brain informatics
  • Year:
  • 2009

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Abstract

In this paper, we present an investigation on heuristics retrieval in human problem solving by combining the computational cognitive model ACT-R (Adaptive Control of Thought-Rational) and advanced fMRI (functional Magnetic Resonance Imaging) brain imaging technique. As a new paradigm, 4*4 Sudoku is developed to facilitate this study, in which seven heuristics that can be classified into 3 groups are designed to solve two types of tasks: simple and complex ones. The cognitive processes of the two types of 4*4 Sudoku tasks are explored based on the outputs of ACT-R model. This study shows that several key elements take important roles in the retrieval of heuristics, including the ways of problem presentation, complexity of heuristics and status of goal. The fitness of model prediction to real participants' data on behavior and BOLD (Blood Oxygenation Level-Dependent) response in five predefined brain regions illustrates that our hypotheses and results are acceptable. This work is a significant step towards tackling the puzzle of the heuristics retrieval in human brain.