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286
The complexity of computing a Nash equilibrium
, 2006
"... We resolve the question of the complexity of Nash equilibrium by showing that the problem of computing a Nash equilibrium in a game with 4 or more players is complete for the complexity class PPAD. Our proof uses ideas from the recentlyestablished equivalence between polynomialtime solvability of n ..."
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Cited by 329 (23 self)
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We resolve the question of the complexity of Nash equilibrium by showing that the problem of computing a Nash equilibrium in a game with 4 or more players is complete for the complexity class PPAD. Our proof uses ideas from the recentlyestablished equivalence between polynomialtime solvability of normalform games and graphical games, and shows that these kinds of games can implement arbitrary members of a PPADcomplete class of Brouwer functions. 1
Multiagent influence diagrams for representing and solving games
 GAMES AND ECONOMIC BEHAVIOR
, 2001
"... The traditional representations of games using the extensive form or the strategic (normal) form obscure much of the structure that is present in realworld games. In this paper, we propose a new representation language for general multiplayer games — multiagent influence diagrams (MAIDs). This rep ..."
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Cited by 188 (2 self)
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The traditional representations of games using the extensive form or the strategic (normal) form obscure much of the structure that is present in realworld games. In this paper, we propose a new representation language for general multiplayer games — multiagent influence diagrams (MAIDs). This representation extends graphical models for probability distributions to a multiagent decisionmaking context. MAIDs explicitly encode structure involving the dependence relationships among variables. As a consequence, we can define a notion of strategic relevance of one decision variable to another: ¢¡ is strategically relevant to if, to optimize the decision rule at, the decision maker needs to take into consideration the decision rule at ¡. We provide a sound and complete graphical criterion for determining strategic relevance. We then show how strategic relevance can be used to detect structure in games, allowing a large game to be broken up into a set of interacting smaller games, which can be solved in sequence. We show that this decomposition can lead to substantial savings in the computational cost of finding Nash equilibria in these games.
Settling the complexity of twoplayer Nash equilibrium.
 Proc. 47th FOCS,
, 2006
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Computing the optimal strategy to commit to
 IN PROCEEDINGS OF THE 7TH ACM CONFERENCE ON ELECTRONIC COMMERCE (ACMEC
, 2006
"... In multiagent systems, strategic settings are often analyzed under the assumption that the players choose their strategies simultaneously. However, this model is not always realistic. In many settings, one player is able to commit to a strategy before the other player makes a decision. Such models a ..."
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Cited by 145 (21 self)
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In multiagent systems, strategic settings are often analyzed under the assumption that the players choose their strategies simultaneously. However, this model is not always realistic. In many settings, one player is able to commit to a strategy before the other player makes a decision. Such models are synonymously referred to as leadership, commitment, or Stackelberg models, and optimal play in such models is often significantly different from optimal play in the model where strategies are selected simultaneously. The recent surge in interest in computing gametheoretic solutions has so far ignored leadership models (with the exception of the interest in mechanism design, where the designer is implicitly in a leadership position). In this paper, we study how to compute optimal strategies to commit to under both commitment to pure strategies and commitment to mixed strategies, in both normalform and Bayesian games. We give both positive results (efficient algorithms) and negative results (NPhardness results).
Nash QLearning for GeneralSum Stochastic Games
 JOURNAL OF MACHINE LEARNING RESEARCH
, 2003
"... We extend Qlearning to a noncooperative multiagent context, using the framework of generalsum stochastic games. A learning agent maintains Qfunctions over joint actions, and performs updates based on assuming Nash equilibrium behavior over the current Qvalues. This learning protocol provably conv ..."
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Cited by 138 (0 self)
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We extend Qlearning to a noncooperative multiagent context, using the framework of generalsum stochastic games. A learning agent maintains Qfunctions over joint actions, and performs updates based on assuming Nash equilibrium behavior over the current Qvalues. This learning protocol provably converges given certain restrictions on the stage games (defined by Qvalues) that arise during learning. Experiments with a pair of twoplayer grid games suggest that such restrictions on the game structure are not necessarily required. Stage games encountered during learning in both grid environments violate the conditions. However, learning consistently converges in the first grid game, which has a unique equilibrium Qfunction, but sometimes fails to converge in the second, which has three different equilibrium Qfunctions. In a comparison of offline learning performance in both games, we find agents are more likely to reach a joint optimal path with Nash Qlearning than with a singleagent Qlearning method. When at least one agent adopts Nash Qlearning, the performance of both agents is better than using singleagent Qlearning. We have also implemented an online version of Nash Qlearning that balances exploration with exploitation, yielding improved performance.
Complexity Results about Nash Equilibria
, 2002
"... Noncooperative game theory provides a normative framework for analyzing strategic interactions. ..."
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Cited by 135 (10 self)
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Noncooperative game theory provides a normative framework for analyzing strategic interactions.
Playing large games using simple strategies
 IN: PROC. OF THE 4TH ACM CONF. ON EL. COMMERCE (EC ’03). ASSOC. OF COMP. MACH
, 2003
"... We prove the existence of Nash equilibrium strategies with support logarithmic in the number of pure strategies. We also show that the payoffs to all players in any (exact) Nash equilibrium can be approximated by the payoffs to the players in some such logarithmic support Nash equilibrium. These ..."
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Cited by 122 (4 self)
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We prove the existence of Nash equilibrium strategies with support logarithmic in the number of pure strategies. We also show that the payoffs to all players in any (exact) Nash equilibrium can be approximated by the payoffs to the players in some such logarithmic support Nash equilibrium. These strategies are also uniform on a multiset of logarithmic size and therefore this leads to a quasipolynomial algorithm for computing an Nash equilibrium. To our knowledge this is the rst subexponential algorithm for finding an Nash equilibrium. Our results hold for any multipleplayer game as long as the number of players is a constant (i.e., it is independent of the number of pure strategies). A similar argument also proves that for a xed number of players m, the payos to all players in any mtuple of mixed strategies can be approximated by the payos in some mtuple of constant support strategies. We also prove that if the payoff matrices of a two person game have low rank then the game has an exact Nash equilibrium with small support. This implies that if the payoff matrices can be well approximated by low rank matrices, the game has an equilibrium with small support. It also implies that if the payo matrices have constant rank we can compute an exact Nash equilibrium in polynomial time.
Computing correlated equilibria in MultiPlayer Games
 STOC'05
, 2005
"... We develop a polynomialtime algorithm for finding correlated equilibria (a wellstudied notion of rationality due to Aumann that generalizes the Nash equilibrium) in a broad class of succinctly representable multiplayer games, encompassing essentially all known kinds, including all graphical games, ..."
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Cited by 96 (6 self)
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We develop a polynomialtime algorithm for finding correlated equilibria (a wellstudied notion of rationality due to Aumann that generalizes the Nash equilibrium) in a broad class of succinctly representable multiplayer games, encompassing essentially all known kinds, including all graphical games, polymatrix games, congestion games, scheduling games, local effect games, as well as several generalizations. Our algorithm is based on a variant of the existence proof due to Hart and Schmeidler [11], and employs linear programming duality, the ellipsoid algorithm, Markov chain steady state computations, as well as applicationspecific methods for computing multivariate expectations.
Settling the Complexity of Computing TwoPlayer Nash Equilibria
"... We prove that Bimatrix, the problem of finding a Nash equilibrium in a twoplayer game, is complete for the complexity class PPAD (Polynomial Parity Argument, Directed version) introduced by Papadimitriou in 1991. Our result, building upon the work of Daskalakis, Goldberg, and Papadimitriou on the c ..."
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Cited by 88 (5 self)
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We prove that Bimatrix, the problem of finding a Nash equilibrium in a twoplayer game, is complete for the complexity class PPAD (Polynomial Parity Argument, Directed version) introduced by Papadimitriou in 1991. Our result, building upon the work of Daskalakis, Goldberg, and Papadimitriou on the complexity of fourplayer Nash equilibria [21], settles a long standing open problem in algorithmic game theory. It also serves as a starting point for a series of results concerning the complexity of twoplayer Nash equilibria. In particular, we prove the following theorems: • Bimatrix does not have a fully polynomialtime approximation scheme unless every problem in PPAD is solvable in polynomial time. • The smoothed complexity of the classic LemkeHowson algorithm and, in fact, of any algorithm for Bimatrix is not polynomial unless every problem in PPAD is solvable in randomized polynomial time. Our results also have a complexity implication in mathematical economics: • ArrowDebreu market equilibria are PPADhard to compute.