
Generalized Cops and Robbers: A MultiPlayer Pursuit Game on Graphs
We introduce and study the Generalized Cops and Robbers game (GCR), an N...
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Correlated Equilibria for Approximate Variational Inference in MRFs
Almost all of the work in graphical models for game theory has mirrored ...
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The Multiplayer Colonel Blotto Game
We initiate the study of the natural multiplayer generalization of the c...
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A RealTime Game Theoretic Planner for Autonomous TwoPlayer Drone Racing
To be successful in multiplayer drone racing, a player must not only fo...
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Coalition Resilient Outcomes in Max kCut Games
We investigate strong Nash equilibria in the max kcut game, where we ar...
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A Game Theoretic Approach to Autonomous TwoPlayer Drone Racing
To be successful in multiplayer drone racing, a player must not only fo...
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FaultTolerant Hotelling Games
The nplayer Hotelling game calls for each player to choose a point on t...
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Graphical Models for Game Theory
In this work, we introduce graphical modelsfor multiplayer game theory, and give powerful algorithms for computing their Nash equilibria in certain cases. An nplayer game is given by an undirected graph on n nodes and a set of n local matrices. The interpretation is that the payoff to player i is determined entirely by the actions of player i and his neighbors in the graph, and thus the payoff matrix to player i is indexed only by these players. We thus view the global nplayer game as being composed of interacting local games, each involving many fewer players. Each player's action may have global impact, but it occurs through the propagation of local influences.Our main technical result is an efficient algorithm for computing Nash equilibria when the underlying graph is a tree (or can be turned into a tree with few node mergings). The algorithm runs in time polynomial in the size of the representation (the graph and theassociated local game matrices), and comes in two related but distinct flavors. The first version involves an approximation step, and computes a representation of all approximate Nash equilibria (of which there may be an exponential number in general). The second version allows the exact computation of Nash equilibria at the expense of weakened complexity bounds. The algorithm requires only local messagepassing between nodes (and thus can be implemented by the players themselves in a distributed manner). Despite an analogy to inference in Bayes nets that we develop, the analysis of our algorithm is more involved than that for the polytree algorithm in, owing partially to the fact that we must either compute, or select from, an exponential number of potential solutions. We discuss a number of extensions, such as the computation of equilibria with desirable global properties (e.g. maximizing global return), and directions for further research.
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