➭ Number of influencers \(n\):

➭ Number of victims \(m\):

➭ Influencer network \(I \in \left[0, 1\right]^{n \times n}\):

➭ Influence weights \(W \in \left[0, 1\right]^{n \times m}\):

➭ Victim network \(V \in \left[0, 1\right]^{m \times m}\):

➭ Victim weights \(U \in \left[0, 1\right]^{m \times n}\):

➭ Influencer targets \(t\):

➭ Influencers positions \(x\):

➭ Victims positions \(y\):

➭ Influencers best response dynamics:

➭ Victims best response dynamics:

➭ Influencer \(i\)'s payoff given action \(x_{i}\): \(\displaystyle\sum_{j'} W\left(i, j'\right) \left\|t_{i} - y_{j'}\right\|^{2} + \lambda \displaystyle\sum_{i'} I\left(i, i'\right) \left\|x_{i} - x_{i'}\right\|^{2}\)

➭ Victim \(j\)'s payoff given action \(y_{j}\): \(\displaystyle\sum_{i'} U\left(j, i'\right) \left\|y_{j} - x_{i'}\right\|^{2} + \rho \displaystyle\sum_{j'} V\left(j, j'\right) \left\|y_{j} - y_{j'}\right\|^{2}\)

➭ Influencer weight on neighbors \(\lambda\):

➭ Victim weight on neighbors \(\rho\):