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- Type of Document: Ph.D. Dissertation
- Language: Farsi
- Document No: 48034 (19)
- University: Sharif University of Technology
- Department: Computer Engineering
- Advisor(s): Habibi, Jafar
- Abstract:
- Controlling dynamical systems is an important area of research, having many applications in related practical fields. One class of dynamical systems which have obtained ever-growing importance in recent years are networked dynamical systems, in which dynamic behavior is observed on nodes interacting in a networked setting. This is mainly due to the rise of complex networks, e.g. social networks, as an important and powerful method of capturing dynamic behavior that exists in different systems. One important aspect of such systems is that in many scenarios, actors that participate in them are selfish and act rationally based on their own self interest. Therefore guiding such systems to desirable states which may not be in the direct interest of the actors is a challenging and complex task.To model the interactions of the actors in this context, game theory is used.Whilst classic game theory deals with static systems where the goal is to reach an equilibrium, an important subbranch of this area of research focuses more on the dynamics of reaching this equilibrium state. Therefore best response dynamics is used where in each round one actor, here referred to as a player, choses a best response keeping in mind his own utilization function and the current state of the network, i.e. each node’s local state and also the state of edges between nodes. In this thesis, we propose different methods based on combinatorial optimization to control the best response dynamics that ensues network games. In general, our target control problem is defined as an optimization problem which tries to find best values for the overall global parameters of the dynamical system which maximize a global objective function that calculates the desirability of the networks’ state for us. In this thesis, different control parameters are considered, including 1) the initial setting of the dynamical system, 2) the underlying network, 3) the order in which players can take turns, 4) the cost parameters that can be used to penalize a player for some chosen action and 5) the set of players who are permitted to play. Therefore we can use the optimal values of these control parameters so that the interaction of the selfish players reaches a final equilibrium that is acceptable to us
- Keywords:
- Game Theory ; Social Networks ; Graph Theory ; Combinatorial Optimization ; Best Response Games
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