Controllability and observability of Boolean control networks
Automatica (Journal of IFAC)
Input-state approach to boolean networks
IEEE Transactions on Neural Networks
Complexity and stochastic evolution of dyadic networks
Computers and Operations Research
Mean Field Games: Numerical Methods
SIAM Journal on Numerical Analysis
Brief paper: Controllability of Boolean control networks with time delays in states
Automatica (Journal of IFAC)
Automatica (Journal of IFAC)
Disturbance decoupling of mix-valued logical networks via the semi-tensor product method
Automatica (Journal of IFAC)
On reachability and controllability of switched Boolean control networks
Automatica (Journal of IFAC)
Automatica (Journal of IFAC)
Controller design for disturbance decoupling of Boolean control networks
Automatica (Journal of IFAC)
Hi-index | 22.14 |
Using the semi-tensor product method, this paper investigates the algebraic formulation and strategy optimization for a class of evolutionary networked games with ''myopic best response adjustment'' rule, and presents a number of new results. First, the dynamics of the evolutionary networked game is converted to an algebraic form via the semi-tensor product, and an algorithm is established to construct the algebraic formulation for the game. Second, based on the algebraic form, the dynamical behavior of evolutionary networked games is discussed, and some interesting results are presented. Finally, the strategy optimization problem is considered by adding a pseudo-player to the game, and a free-type control sequence is designed to maximize the average payoff of the pseudo-player. The study of an illustrative example shows that the new results obtained in this paper work very well.