We develop a probabilistic approach to continuous-time finite state mean field games. Based on an alternative description of continuous-time Markov chain by means of semimartingale and the weak formulation of stochastic optimal control, our approach not only allows us to tackle the mean field of states and the mean field of control in the same time, but also extend the strategy set of players from Markov strategies to closed-loop strategies. We show the existence and uniqueness of Nash equilibrium for the mean field game, as well as how the equilibrium of mean field game consists of an approximative Nash equilibrium for the game with finite number of players under different assumptions of structure and regularity on the cost functions and transition rate between states. 
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                            Social Cost Analysis of Shared/Buy-in Computing Systems
                        
                    
    
            Shared/buy-in computing systems offer users the option to select between buy-in and shared services. In such systems, idle buy-in resources are made available to other users for sharing. With strategic users, resource purchase and allocation in such systems can be cast as a non-cooperative game, whose corresponding Nash equilibrium does not necessarily result in the optimal social cost. In this study, we first derive the optimal social cost of the game in closed form, by casting it as a convex optimization problem and establishing related properties. Next, we derive a closed-form expression for the social cost at the Nash equilibrium, and show that it can be computed in linear time. We further show that the strategy profiles of users at the optimum and the Nash equilibrium are directly proportional. We measure the inefficiency of the Nash equilibrium through the price of anarchy, and show that it can be quite large in certain cases, e.g., when the operating expense ratio is low or when the distribution of user workloads is relatively homogeneous. To improve the efficiency of the system, we propose and analyze two subsidy policies, which are shown to converge using best-response dynamics. 
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                            - Award ID(s):
 - 1908087
 
- PAR ID:
 - 10496686
 
- Publisher / Repository:
 - IEEE
 
- Date Published:
 
- Journal Name:
 - ACM Transactions on Economics and Computation
 
- Volume:
 - 11
 
- Issue:
 - 3-4
 
- ISSN:
 - 2167-8375
 
- Page Range / eLocation ID:
 - 1 to 36
 
- Format(s):
 - Medium: X
 
- Sponsoring Org:
 - National Science Foundation
 
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