Game theory is not like the reinforcement learning which we have just talked about. In the game theory, the condition that one is playing against someone else is considered. Furthermore, game theory is not about learning, it does not learn from data or previous instances, but tries to figure out what to do given a specific game rule. A game could be described using a game matrix. The two player...

We prove that the class of GUM matrices is the largest class of bi-potential matrices stable under Hadamard increasing functions. We also show that any power α ≥ 1, in the sense of Hadamard functions, of an inverseM -matrix is also inverseM matrix showing a conjecture stated in Neumann [15]. We study the class of filtered matrices, which include naturally the GUM matrices, and present some suff...

In this paper, we propose a new linear complementarity problem named as bi-linear complementarity problem (BLCP) and the method for solving BLCP. In addition, the algorithm for error estimation of BLCP is also given. Numerical experiments show that the algorithm is efficient. Keywords—Bi-linear complementarity problem, Linear complementarity problem, Extended linear complementarity problem, Err...

The purpose of this paper is to develop a methodology for solving a new type of matrix games in which payoffs are expressed with triangular intuitionistic fuzzy numbers (TIFNs). In this methodology, the concept of solutions for matrix games with payoffs of TIFNs is introduced. A pair of auxiliary intuitionistic fuzzy programming models for players are established to determine optimal strategies...

In this paper, we consider an interval matrix game with interval valued payoffs, which is the generation of the traditional matrix game. The “saddle-points”of this interval matrix game are defined and characterized as equilibrium points of corresponding non-zero sum parametric games. Numerical examples are given to illustrate our idea. These results are extended to the fuzzy matrix games. Also,...

Shannon's entropy has been characterized in several ways. Kaminski and Mikusihski [5] simplified Fadeev's [3] approach by considering, what they called the entropy equation: (1.1) H(x, y, z) = H(x + y, 0, z) + H(x, y, 0) , (x ^ 0 , y ^ 0 , z > 0 , xy + yz + zx > 0) . A general continuous symmetric solution of (1.1) given by (1.2) H(x, y, z) = (x + y + z) log (x + y + z) — x log x y log y — z lo...

In this paper, we present new variants of global bi-conjugate gradient (Gl-BiCG) and global bi-conjugate residual (Gl-BiCR) methods for solving nonsymmetric linear systems with multiple right-hand sides. These methods are based on global oblique projections of the initial residual onto a matrix Krylov subspace. It is shown that these new algorithms converge faster and more smoothly than the Gl-...

The purpose of this paper is to develop an effective methodology for solving constrained matrix games with payoffs of trapezoidal fuzzy numbers (TrFNs), which are a type of two-person non-cooperative games with payoffs expressed by TrFNs and players’ strategies being constrained. In this methodology, it is proven that any Alfa-constrained matrix game has an interval-type value and hereby any co...

Matrix game theory is concerned with how two players make decisions when they are faced with known exact payoffs. The aim of this paper is to develop a simple and an effective linear programming method for solving matrix games in which the payoffs are expressed with intervals. Because the payoffs of the matrix game are intervals, the value of the matrix game is an interval as well. Based on the...

This Mostly, factorization of matrices is not unique, Non-negative Matrix Factorization (NMF) changes from the Principal Component Analysis, Singular Value Decomposition, Nystrom Method, and it imposes the controls that the factors must be non-negative. The proposed method utilizes a most powerful tool derivative from evolutionary game theory, which permits re-organizing the clustering attained...