Simulating Human Heuristic Problem Solving: A Study by Combining ACT-R and fMRI Brain Image - Brain Informatics - page 53

Simulating Human Heuristic Problem Solving: A
Study by Combining ACT-R and fMRI Brain
Image

Rifeng Wang 1 , 2 ,JieXiang 3 , 1 ,HaiyanZhou 1 , Yulin Qin 1 , 4 , and Ning Zhong 1 , 5

1 The International WIC Institute, Beijing University of Technology, China
2 Dept of Computer Science, Guangxi University of Technology, China
3 College of Computer and Software, Taiyuan University of Technology, China
4 Dept of Psychology, Carnegie Mellon University, USA
5 Dept of Life Science and Informatics, Maebashi Institute of Technology, Japan
[e-mail], [e-mail]

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 imag-
ing 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 behav-
ior 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.

1 Introduction

Human problem solving, one of the important research issues in cognitive science
and computer science especially in artificial intelligence (AI), has been studied
for dozens of years [2, 7, 8, 12, 13, 15]. In their book [8], Newell and Simon ob-
served that human being always uses heuristic strategy when solving a complex
problem, such as chess. Heuristic searching strategy is also a popular method
in AI, such as in solving traveling salesman problem [12], flow shops scheduling
problem [7], and so on. MaCarthy pointed out that the largest qualitative gap
between human performance and computer performance is in the area of heuris-
tics [9]. One puzzle on problem solving is that how human brain retrieves and
uses heuristics to speed up problem solving. The answer of this question may
shed light on developing new model for Web-based information retrieving (IR),
Web-based reasoning technology [16, 17]. This paper focuses on this question and