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» Computing Optimal Strategies to Commit to in Stochastic Game...
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AAAI
2008
13 years 10 months ago
Efficient Algorithms to Solve Bayesian Stackelberg Games for Security Applications
In a class of games known as Stackelberg games, one agent (the leader) must commit to a strategy that can be observed by the other agent (the adversary/follower) before the advers...
Praveen Paruchuri, Jonathan P. Pearce, Janusz Mare...
GLOBECOM
2009
IEEE
13 years 5 months ago
Dogfight in Spectrum: Jamming and Anti-Jamming in Multichannel Cognitive Radio Systems
Primary user emulation attack in multichannel cognitive radio systems is discussed. An attacker is assumed to be able to send primary-user-like signals during spectrum sensing peri...
Husheng Li, Zhu Han
FSTTCS
2010
Springer
13 years 5 months ago
Playing in stochastic environment: from multi-armed bandits to two-player games
Given a zero-sum infinite game we examine the question if players have optimal memoryless deterministic strategies. It turns out that under some general conditions the problem for...
Wieslaw Zielonka
ATAL
2006
Springer
13 years 11 months ago
Learning to commit in repeated games
Learning to converge to an efficient, i.e., Pareto-optimal Nash equilibrium of the repeated game is an open problem in multiagent learning. Our goal is to facilitate the learning ...
Stéphane Airiau, Sandip Sen
ATAL
2007
Springer
14 years 2 months ago
Commitment and extortion
Making commitments, e.g., through promises and threats, enables a player to exploit the strengths of his own strategic position as well as the weaknesses of that of his opponents....
Paul Harrenstein, Felix Brandt, Felix A. Fischer