Network Models of Science Compare Pluralist vs. Monist Agents in Belief Dynamics
This paper introduces a multi-agent variational inference model to test Feyerabend's theoretical pluralism, comparing communities of agents that can hold rival theories simultaneously against monist agents that maintain a single model. Experiments show how pluralist communities undergo uncertainty and theory shifts, how inter-community communication affects beliefs under differing observations, and how sharing theory support versus sharing beliefs within theories differently shape collective dynamics. The work provides a computational framework for studying scientific belief evolution.
Offers a concrete, novel AI-relevant simulation of scientific belief dynamics with experimental demonstrations, useful for researchers in multi-agent systems and philosophy of science.
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