Abstract

Many decision problems in economics, information technology, and industry can be transformed to an optimal stopping of adapted random vectors with some utility function over the set of Markov times with respect to filtration build by the decision maker's knowledge. The optimal stopping problem formulation is to find a stopping time which maximizes the expected value of the accepted (stopped) random vector's utility. There are natural extensions of optimal stopping problem to stopping the games-the problem of stopping random vectors by two or more decision makers. Various approaches dependent on the information scheme and the aims of the agents in a considered model. This report unifies a group of non-cooperative stopping game models with forced cooperation by the role of the agents, their aims and aspirations (v. Assaf & Samuel-Cahn(1998), Szajowski & Yasuda(1995)) or extensions of the strategy sets (v. Ramsey & Szajowski(2008)).

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