Automatic fuzzy decision making system with learning for competing and connected businesses

We study uncertainties surrounding competition on business networks and board games. We investigate these uncertainties using concepts of fuzzy logic and game theory. We investigate how the payoff of the players is affected by a number of factors. These include the level of connectivity or number of links, the number of competitors, possible constraints on the networks and on the boards, as well as choice of strategy adopted by competitors. We introduce one fuzzy player in the game. This player uses fuzzy rules to make strategic decisions. We introduce learning to train and analyze how the fuzzy player adapts over time during the game.