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CDC
2008
IEEE

Oblivious equilibrium for large-scale stochastic games with unbounded costs

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Oblivious equilibrium for large-scale stochastic games with unbounded costs
— We study stochastic dynamic games with a large number of players, where players are coupled via their cost functions. A standard solution concept for stochastic games is Markov perfect equilibrium (MPE). In MPE, each player’s strategy is a function of its own state as well as the state of the other players. This makes MPE computationally prohibitive as the number of players becomes large. An approximate solution concept called oblivious equilibrium (OE) was introduced in [1], where each player’s decision depends only on its own state and the “long-run average” state of other players. This makes OE computationally more tractable than MPE. It was shown in [1] that, under a set of assumptions, as the number of players become large, OE closely approximates MPE. In this paper we relax those assumptions and generalize that result to cases where the cost functions are unbounded. Furthermore, we show that under these relaxed set of assumptions, the OE approximation result can be ap...
Sachin Adlakha, Ramesh Johari, Gabriel Y. Weintrau
Added 29 May 2010
Updated 29 May 2010
Type Conference
Year 2008
Where CDC
Authors Sachin Adlakha, Ramesh Johari, Gabriel Y. Weintraub, Andrea J. Goldsmith
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