Searching far away from the lamp-post: An agent-based model
Authored by Oana Vuculescu
Date Published: 2017
DOI: 10.1177/1476127016669869
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Abstract
This article presents insights from a laboratory experiment on human
problem solving in a combinatorial task. I rely on a hierarchical rugged
landscape to explore how human problem-solvers are able to detect and
exploit patterns in their search for an optimal solution. Empirical
findings suggest that solvers do not engage only in local and random
distant search, but as they accumulate information about the problem
structure, solvers make model-based' moves, a type of cognitive search.
I then calibrate an agent-based model of search to analyse and interpret
the findings from the experimental setup and discuss implications for
organizational search. Simulation results show that, for non-trivial
problems, performance can be increased by a low level of persistence,
that is, an increased likelihood to quickly abandon unsuccessful paths.
Tags
Agent-based modelling
knowledge
Exploitation
Exploration
Computer simulations
open innovation
habits
cognition
research methods
Capabilities
Brain
Experimental design or
analysis
Evolutionary theory
Knowledge
creation
Topics and perspectives
Insight