Consensus and Disagreement of Heterogeneous Belief Systems in Influence NetworksYe, B., Liu, J., Wang, L., Anderson, B. D. O. & Cao, M., 1-Nov-2020, In : IEEE-Transactions on Automatic Control. 65, 11, p. 4679-4694 16 p., 8941271.
Research output: Contribution to journal › Article › Academic › peer-review
Recently, an opinion dynamics model has been proposed to describe a network of individuals discussing a set of logically interdependent topics. For each individual, the set of topics and the logical interdependencies between the topics (captured by a logic matrix) form a belief system. We investigate the role the logic matrix and its structure plays in determining the final opinions, including existence of the limiting opinions, of a strongly connected network of individuals. We provide a set of results that, given a set of individuals' belief systems, allow a systematic determination of which topics will reach a consensus, and of which topics will disagreement arise. For irreducible logic matrices, each topic reaches a consensus. For reducible logic matrices, which indicates a cascade interdependence relationship, conditions are given on whether a topic will reach a consensus or not. It turns out that heterogeneity among the individuals' logic matrices, and a cascade interdependence relationship, are necessary conditions for disagreement. Thus, this article attributes for the first time, a strong diversity of limiting opinions to heterogeneity of belief systems in influence networks, in addition to the more typical explanation that strong diversity arises from individual stubbornness.
|Number of pages||16|
|Journal||IEEE-Transactions on Automatic Control|
|Publication status||Published - 1-Nov-2020|
|Event|| IEEE Transactions on Automatic Control - |
Duration: 24-Dec-2019 → 24-Dec-2019
IEEE Transactions on Automatic Control
24/12/2019 → 24/12/2019
- Agent-based models, influence networks, multiagent systems, opinion dynamics, social networks