The success of the alpha-beta algorithm in game-playing has shown its value for problem solving in artiicial intelligence, especially in the domain of two-person zero-sum games with perfect-information. However, there exist diierent algorithms for game-tree search. This paper describes and assesses those proposed alternatives according to how they try to overcome the limitations of alpha-beta. ...

This paper deals with the problem of designing a rapid transit network that reacts as well as possible to link failures. It is assumed that when a link fails, another path or another transportation mode is provided to transport passengers between the endpoints of the affected link. The goal is to build a network that attracts as many passengers as possible when a failure occurs. The problem is ...

The classic minimax search for two-player zero-sum games such as chess has been thoroughly studied since the early years of AI; however for more general nonzero-sum games, minimax is non-optimal, given a player’s knowledge about the opponent. Previously, a few opponent models and algorithms such as M were introduced to improve minimax by simulating the opponent’s search, given the opponent’s st...

Two-person zero-sum stochastic games with finite state and action spaces are considered. The expected average payoff criterion is used for multichain structures. In the special caae that only one player controls the transitions, it is shown that the optimal stationary policies and the value of the game can be obtained from the optimal solutions to a pair of dual linear programs. A decomposition...

We study how continuous time Bertrand and Cournot competitions, in which firms producing similar goods compete with one another by setting prices or quantities respectively, can be analyzed as continuum dynamic mean field games. Interactions are of mean field type in the sense that the demand faced by a producer is affected by the others through their average price or quantity. Motivated by ene...

In this paper, we investigate the use of reciprocative strategy to induce cooperative behavior in non-zero-sum games. Reciprocative behavior is defined mathematically in the context of a two-person non-zero-sum game in which both the players have a common set of pure strategies. Conditions under which mutual cooperative behavior results when one of the players responds optimally to reciprocativ...

It is well documented in the literature that inadequacy of the analytical models has been a primary reason for the low economic stability of deregulated power industry. Some of the modeling inadequacies can be attributed to the difficulties of analyzing nonzero sum multiplayer stochastic games that are inherent in deregulated power market operations. This paper presents a two-tier game theoreti...

Multistage robust optimization problems can be interpreted as two-person zero-sum games between two players. We exploit this game-like nature and utilize a game tree search in order to solve quantified integer programs (QIPs). In algorithmic environment relaxations are repeatedly called asses the quality of branching variable for generation bounds. A useful relaxation, however, must well balanc...

The paper is concerned with two-person zero-sum mean-field linear-quadratic stochastic differential games over finite horizons. By a Hilbert space method, necessary condition and sufficient are derived for the existence of an open-loop saddle point. It shown that under condition, associated two Riccati equations admit unique strongly regular solutions, in terms which point can be represented as...