4,036 research outputs found
A Parameterisation of Algorithms for Distributed Constraint Optimisation via Potential Games
This paper introduces a parameterisation of learning algorithms for distributed constraint optimisation problems (DCOPs). This parameterisation encompasses many algorithms developed in both the computer science and game theory literatures. It is built on our insight that when formulated as noncooperative games, DCOPs form a subset of the class of potential games. This result allows us to prove convergence properties of algorithms developed in the computer science literature using game theoretic methods. Furthermore, our parameterisation can assist system designers by making the pros and cons of, and the synergies between, the various DCOP algorithm components clear
A Lyapunov Optimization Approach to Repeated Stochastic Games
This paper considers a time-varying game with players. Every time slot,
players observe their own random events and then take a control action. The
events and control actions affect the individual utilities earned by each
player. The goal is to maximize a concave function of time average utilities
subject to equilibrium constraints. Specifically, participating players are
provided access to a common source of randomness from which they can optimally
correlate their decisions. The equilibrium constraints incentivize
participation by ensuring that players cannot earn more utility if they choose
not to participate. This form of equilibrium is similar to the notions of Nash
equilibrium and correlated equilibrium, but is simpler to attain. A Lyapunov
method is developed that solves the problem in an online \emph{max-weight}
fashion by selecting actions based on a set of time-varying weights. The
algorithm does not require knowledge of the event probabilities and has
polynomial convergence time. A similar method can be used to compute a standard
correlated equilibrium, albeit with increased complexity.Comment: 13 pages, this version fixes an incorrect statement of the previous
arxiv version (see footnote 1, page 5 in current version for the correction
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