Abstract
Modern scientific research has become largely a cooperative activity in the Internet age. We build a simulation model to understand the population-level creativity based on the heuristic ant colony algorithm. Each researcher has two heuristic parameters characterizing the goodness of his own judgments and his trust on literature. We study how the distributions of contributor heuristic parameters change with the research problem scale, stage of the research problem, and computing power available. We also identify situations where path dependence and hasty research due to the pressure on productivity can significantly impede the long-term advancement of scientific research. Our work provides some preliminary understanding and guidance for the dynamical process of cooperative scientific research in various disciplines.
Highlights
RESEARCH ARTICLEA model for cooperative scientific research inspired by the ant colony algorithm Zhuoran HeID1,2*, Tingtao Zhou3*
Cooperative scientific research is a new trend in the science community nowadays due to the growth of number of researchers [1,2,3], the faster propagation of knowledge through the Internet [4,5,6,7] and the many new interdisciplinary research topics [8, 9], etc
A model for cooperative scientific research inspired by the ant colony algorithm model inspired by the ant colony optimization (ACO) algorithm [40,41,42] to study the dynamical process of cooperative scientific research by computer simulations
Summary
A model for cooperative scientific research inspired by the ant colony algorithm Zhuoran HeID1,2*, Tingtao Zhou3*. OPEN ACCESS Citation: He Z, Zhou T (2022) A model for cooperative scientific research inspired by the ant colony algorithm. Modern scientific research has become largely a cooperative activity in the Internet age. We build a simulation model to understand the population-level creativity based on the heuristic ant colony algorithm. Each researcher has two heuristic parameters characterizing the goodness of his own judgments and his trust on literature. We study how the distributions of contributor heuristic parameters change with the research problem scale, stage of the research problem, and computing power available. Our work provides some preliminary understanding and guidance for the dynamical process of cooperative scientific research in various disciplines
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