Frontiers of Dynamic Games Game Theory and Management, St. Petersburg, 2019
The content of this volume is mainly based on selected talks that were given at the
“International Meeting on Game Theory (ISDG12-GTM2019),” as joint meeting of
“12th International ISDG Workshop” and “13th International Conference on Game
Theory and Management,” held in St. Petersburg, Russia on July 03–05, 2019. The
meeting was organized by St. Petersburg State University and International Society
of Dynamic Games (ISDG).
Every year starting from 2007, an international conference “Game Theory and
Management” (GTM) has taken place at the Saint Petersburg State University.
Among the plenary speakers of this conference series were the Nobel Prize winners
Robert Aumann, John Nash, Reinhard Selten, Roger Myerson, Finn Kidland, Eric
Maskin, and many other famous game theorists. The underlying theme of the
conferences is the promotion of advanced methods for modeling the behavior that
each agent (also called player) has to adopt in order to maximize his or her reward
once the reward does not only depend on the individual choices of a player (or a
group of players), but also on the decisions of all agents that are involved in the
In this paper we introduce stochastic parameters into the network game model with production and knowledge externalities. This model was proposed by V. Matveenko and A. Korolev as a generalization of the two-period Romer model. Agents differ in their productivities which have deterministic and stochastic (Wiener) components. We study the dynamics of a single agent and the dynamics of a dyad where two agents are aggregated. We derive explicit expressions for the dynamics of a single agent and dyad dynamics in the form of Brownian random processes, and qualitatively analyze the solutions of stochastic equations and systems of stochastic equations.
To enforce the long-term cooperation in a multistage multicriteria game we use the imputation distribution procedure (IDP) based approach. We mainly focus on such useful properties of the IDP like “reward immediately after the move” assumption, time consistency inequality, efficiency and non-negativity constraint. To overcome the problem of negative payments along the optimal cooperative trajectory the novel refined A-incremental IDP is designed. We establish the properties of the proposed A-incremental payment schedule and provide an illustrative example to clarify how the algorithm works.