  To model the interdependent couplings of multiple topics, we develop a set of
rules for opinion updates of a group of agents. The rules are used to design or
assign values to the elements of interdependent weighting matrices. The
cooperative and anti-cooperative couplings are modeled in both the
inverse-proportional and proportional feedbacks. The behaviors of cooperative
opinion dynamics are analyzed using a null space property of state-dependent
matrix-weighted Laplacian matrices and a Lyapunov candidate. Various consensus
properties of state-dependent matrix-weighted Laplacian matrices are predicted
according to the intra-agent network topology and inter-dependency topical
coupling topologies.
