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Rationalizable Strategic Behavior and the Problem of Perfection
Rationalizable Strategic Behavior and the Problem of Perfection

A Recurrent Neural Network for Game Theoretic Decision Making
A Recurrent Neural Network for Game Theoretic Decision Making

gameth1, October 4, 2001 - latest version
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Extensive Form Correlated Equilibrium: Definition and

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PROBLEM SET #7 1. A dominant strategy is a strategy that A. results

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16.410 Lecture 24: Sequential Games

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1 Mixed strategies in 2 ! 2 games 2 Maximin Strategies in zero sum

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... Suppose an individual has $10,000 to invest between a stock and a bond. The stock is a financial asset which has a variable return that is uniformly distributed with an average return of 8.525% and a standard deviation of 3.767%. The bond returns 8.5% with certainty. Denote by 0 ≤ s ≤ 1 be the propo ...
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N-1 - bYTEBoss

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NECTAR: Nash Equilibrium Computation Algorithms
NECTAR: Nash Equilibrium Computation Algorithms

... player to play according to the prescribed strategy while others are playing according to the given strategy profile. In short, any player is not better off by unilateral deviation. Formally, the strategy profile s∗ = (s1∗, s2∗ , . . . , sn∗) is said to be a Nash equilibrium of G if, ui(si∗,s-i∗) ≥ ...
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Artificial Intelligence Games- Outline Games vs. search problems

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ml_3_2010 - Yilmaz Kilicaslan

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Coarse-Grained ParallelGeneticAlgorithm to solve the Shortest Path

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Chapter 1 - University of St. Thomas

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Output Agreement Mechanisms and Common Knowledge

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Minimax

Minimax (sometimes MinMax or MM) is a decision rule used in decision theory, game theory, statistics and philosophy for minimizing the possible loss for a worst case (maximum loss) scenario. Originally formulated for two-player zero-sum game theory, covering both the cases where players take alternate moves and those where they make simultaneous moves, it has also been extended to more complex games and to general decision making in the presence of uncertainty.
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