Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: In the coordination/consensus problem for multi-agent systems, a ll-known condition of achieving consensus is the presence of a spanning arborescence in the communication digraph. The paper deals with the discrete consensus problem in the case where this condition is not satisfied. A characterization of the subspace T P of initial opinions (where P is the influence matrix) that ensure consensus in the DeGroot model is given.  propose a method of coordination that consists of: (1) the transformation of the vector of initial opinions into a vector belonging to T P by orthogonal projection and (2) subsequent iterations of the transformation P. The properties of this method are studied. It is shown that for any non-periodic stochastic matrix P, the resulting matrix of the orthogonal projection method can be treated as a regularized por limit of P.
['Rafig Agaev', 'P. Yu. Chebotarev']
I am writing a research paper on a idea The projection method for reaching consensus and the regularized power limit of a stochastic matrix
[{"from": "human", "value": "I am writing a research paper on a idea The projection method for reaching consensus and the regularized power limit of a stochastic matrix"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: In the coordination/consensus problem for multi-agent systems, a ll-known condition of achieving consensus is the presence of a spanning arborescence in the communication digraph. The paper deals with the discrete consensus problem in the case where this condition is not satisfied. A characterization of the subspace T P of initial opinions (where P is the influence matrix) that ensure consensus in the DeGroot model is given.  propose a method of coordination that consists of: (1) the transformation of the vector of initial opinions into a vector belonging to T P by orthogonal projection and (2) subsequent iterations of the transformation P. The properties of this method are studied. It is shown that for any non-periodic stochastic matrix P, the resulting matrix of the orthogonal projection method can be treated as a regularized por limit of P."}]