| Popis: |
Everyday problems like washing your hands, tying your shoelaces, or cooking dinner can be simple to solve if somebody shows or tells you how, but formidable in the absence of guidance. People depend on algorithmic solutions to physical and computational problems inherited through social learning, yet we do not understand the mechanisms that make the emergence of complex algorithms possible: how do problem-solving algorithms emerge and spread in populations, despite being potentially difficult to discover and even harder to transmit to new people? In this experiment, participants in social networks engage in a problem solving task and transmit their solutions to other people in the network. All participants will have the opportunity to learn from multiple previous participants in the network, and to practice and innovate solutions to the task themselves. Our key question is whether the availability of information about previous participants’ performance on the task influences the population’s ability to discover and maintain performant problem-solving algorithms. We ask the following research question: RQ1: Does the capacity to choose to learn from successful individuals improve the performance of a population on a problem-solving task? |
