Human Search in a Fitness Landscape: How to Assess the Difficulty of a Search Problem
Computational modeling is widely used to study how humans and organizations search and solve problems in fields such as economics, management, cultural evolution, and computer science. We argue that current computational modeling research on human problem-solving needs to address several fundamental...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2020-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2020/7802169 |
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| _version_ | 1832550574225096704 |
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| author | Oana Vuculescu Mads Kock Pedersen Jacob F. Sherson Carsten Bergenholtz |
| author_facet | Oana Vuculescu Mads Kock Pedersen Jacob F. Sherson Carsten Bergenholtz |
| author_sort | Oana Vuculescu |
| collection | DOAJ |
| description | Computational modeling is widely used to study how humans and organizations search and solve problems in fields such as economics, management, cultural evolution, and computer science. We argue that current computational modeling research on human problem-solving needs to address several fundamental issues in order to generate more meaningful and falsifiable contributions. Based on comparative simulations and a new type of visualization of how to assess the nature of the fitness landscape, we address two key assumptions that approaches such as the NK framework rely on: that the NK captures the continuum of the complexity of empirical fitness landscapes and that search behavior is a distinct component, independent from the topology of the fitness landscape. We show the limitations of the most common approach to conceptualize how complex, or rugged, a landscape is, as well as how the nature of the fitness landscape is fundamentally intertwined with search behavior. Finally, we outline broader implications for how to simulate problem-solving. |
| format | Article |
| id | doaj-art-938e45debd6b4e7886987cc3be3a1a12 |
| institution | Kabale University |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-938e45debd6b4e7886987cc3be3a1a122025-02-03T06:06:28ZengWileyComplexity1076-27871099-05262020-01-01202010.1155/2020/78021697802169Human Search in a Fitness Landscape: How to Assess the Difficulty of a Search ProblemOana Vuculescu0Mads Kock Pedersen1Jacob F. Sherson2Carsten Bergenholtz3Department of Management, Aarhus University, Aarhus, DenmarkScienceAtHome, Department of Physics and Astronomy, Aarhus University, Aarhus, DenmarkScienceAtHome, Department of Physics and Astronomy, Aarhus University, Aarhus, DenmarkDepartment of Management, Aarhus University, Aarhus, DenmarkComputational modeling is widely used to study how humans and organizations search and solve problems in fields such as economics, management, cultural evolution, and computer science. We argue that current computational modeling research on human problem-solving needs to address several fundamental issues in order to generate more meaningful and falsifiable contributions. Based on comparative simulations and a new type of visualization of how to assess the nature of the fitness landscape, we address two key assumptions that approaches such as the NK framework rely on: that the NK captures the continuum of the complexity of empirical fitness landscapes and that search behavior is a distinct component, independent from the topology of the fitness landscape. We show the limitations of the most common approach to conceptualize how complex, or rugged, a landscape is, as well as how the nature of the fitness landscape is fundamentally intertwined with search behavior. Finally, we outline broader implications for how to simulate problem-solving.http://dx.doi.org/10.1155/2020/7802169 |
| spellingShingle | Oana Vuculescu Mads Kock Pedersen Jacob F. Sherson Carsten Bergenholtz Human Search in a Fitness Landscape: How to Assess the Difficulty of a Search Problem Complexity |
| title | Human Search in a Fitness Landscape: How to Assess the Difficulty of a Search Problem |
| title_full | Human Search in a Fitness Landscape: How to Assess the Difficulty of a Search Problem |
| title_fullStr | Human Search in a Fitness Landscape: How to Assess the Difficulty of a Search Problem |
| title_full_unstemmed | Human Search in a Fitness Landscape: How to Assess the Difficulty of a Search Problem |
| title_short | Human Search in a Fitness Landscape: How to Assess the Difficulty of a Search Problem |
| title_sort | human search in a fitness landscape how to assess the difficulty of a search problem |
| url | http://dx.doi.org/10.1155/2020/7802169 |
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