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178
On the Complexity of Succinct ZeroSum Games
"... We study the complexity of solving succinct zerosumgames, i.e., the games whose payoff matrix M is given implicitly by a Boolean circuit C such that M (i, j) = C(i, j).We complement the known EXPhardness of computing theexact value of a succinct zerosum game by several results on approximating ..."
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Cited by 17 (0 self)
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We study the complexity of solving succinct zerosumgames, i.e., the games whose payoff matrix M is given implicitly by a Boolean circuit C such that M (i, j) = C(i, j).We complement the known EXPhardness of computing theexact value of a succinct zerosum game by several results on approximating
The Complexity of TwoPerson ZeroSum Games in Extensive Form
 Games and Economic Behavior
, 1990
"... This paper investigates the complexity of finding maxmin strategies for finite twoperson zerosum games in the extensive form. The problem of determining whether a player with imperfect recall can guarantee himself a certain payoff is shown to be NPhard. When both players have imperfect recall ..."
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Cited by 94 (6 self)
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This paper investigates the complexity of finding maxmin strategies for finite twoperson zerosum games in the extensive form. The problem of determining whether a player with imperfect recall can guarantee himself a certain payoff is shown to be NPhard. When both players have imperfect
Adversarial Detection as a ZeroSum Game
 PROC. IEEE CONFERENCE ON DECISION AND CONTROL
, 2012
"... We propose a new game theoretic approach to estimate a binary random variable based on a vector of sensor measurements that may be corrupted by an adversary. The problem is formulated as a zerosum partial information game in which a detector attempts to minimize the probability of error and an att ..."
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Cited by 2 (1 self)
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We propose a new game theoretic approach to estimate a binary random variable based on a vector of sensor measurements that may be corrupted by an adversary. The problem is formulated as a zerosum partial information game in which a detector attempts to minimize the probability of error
Randomized Sampling for Large ZeroSum Games
, 2012
"... This paper addresses the solution of large zerosum matrix games using randomized methods. We formalize a procedure, termed as the sampled security policy (SSP) algorithm, by which a player can compute policies that, with a high confidence, are security policies against an adversary using randomized ..."
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Cited by 4 (3 self)
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This paper addresses the solution of large zerosum matrix games using randomized methods. We formalize a procedure, termed as the sampled security policy (SSP) algorithm, by which a player can compute policies that, with a high confidence, are security policies against an adversary using
Cooperative Reinforcement Learning Based on ZeroSum Games
"... MultiAgent systems (MAS), developed from the artificial intelligent field, include many independent agents, each of which has its own behavior and can achieve a certain goal. The system can be used to solve a complex problem by cooperation and coordination between agents, because most complex probl ..."
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MultiAgent systems (MAS), developed from the artificial intelligent field, include many independent agents, each of which has its own behavior and can achieve a certain goal. The system can be used to solve a complex problem by cooperation and coordination between agents, because most complex
A New Algorithm for Generating Equilibria in Massive ZeroSum Games
, 2007
"... In normal scenarios, computer scientists often consider the number of states in a game to capture the difficulty of learning an equilibrium. However, players do not see games in the same light: most consider Go or Chess to be more complex than Monopoly. In this paper, we discuss a new measure of gam ..."
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Cited by 17 (2 self)
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In normal scenarios, computer scientists often consider the number of states in a game to capture the difficulty of learning an equilibrium. However, players do not see games in the same light: most consider Go or Chess to be more complex than Monopoly. In this paper, we discuss a new measure
Learning in ZeroSum Team Markov Games using Factored Value Functions
 In Neural Information Processing Systems (NIPS
, 2002
"... We present a new method for learning good strategies in zerosum Markov games in which each side is composed of multiple agents collaborating against an opposing team of agents. Our method requires full observability and communication during learning, but the learned policies can be executed in ..."
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Cited by 4 (0 self)
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We present a new method for learning good strategies in zerosum Markov games in which each side is composed of multiple agents collaborating against an opposing team of agents. Our method requires full observability and communication during learning, but the learned policies can be executed
Policy Improvement for Repeated ZeroSum Games with Asymmetric Information
"... Abstract—In a repeated zerosum game, two players repeatedly play the same zerosum game over several stages. We assume that while both players can observe the actions of the other, only one player knows the actual game, which was randomly selected from a set of possible games according to a known d ..."
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Cited by 1 (1 self)
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Abstract—In a repeated zerosum game, two players repeatedly play the same zerosum game over several stages. We assume that while both players can observe the actions of the other, only one player knows the actual game, which was randomly selected from a set of possible games according to a known
Solving ZeroSum Security Games in Discretized SpatioTemporal Domains
"... Among the many deployment areas of Stackelberg Security games, a major area involves games played out in space and time, which includes applications in multiple mobile defender resources protecting multiple mobile targets. Previous algorithms for such spatiotemporal security games fail to scaleup ..."
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Cited by 2 (2 self)
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up and little is known of the computational complexity properties of these problems. This paper provides a novel oraclebased algorithmic framework for a systematic study of different problem variants of computing optimal (minimax) strategies in spatiotemporal security games. Our framework en
Results 1  10
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