3,037 research outputs found
The Complexity of Iterated Strategy Elimination
We consider the computational complexity of the question whether a certain
strategy can be removed from a game by means of iterated elimination of
dominated strategies. In particular, we study the influence of different
definitions of domination and of the number of different payoff values. In
addition, the consequence of restriction to constant-sum games is shown
On Iterated Dominance, Matrix Elimination, and Matched Paths
We study computational problems arising from the iterated removal of weakly
dominated actions in anonymous games. Our main result shows that it is
NP-complete to decide whether an anonymous game with three actions can be
solved via iterated weak dominance. The two-action case can be reformulated as
a natural elimination problem on a matrix, the complexity of which turns out to
be surprisingly difficult to characterize and ultimately remains open. We
however establish connections to a matching problem along paths in a directed
graph, which is computationally hard in general but can also be used to
identify tractable cases of matrix elimination. We finally identify different
classes of anonymous games where iterated dominance is in P and NP-complete,
respectively.Comment: 12 pages, 3 figures, 27th International Symposium on Theoretical
Aspects of Computer Science (STACS
The Complexity of Admissibility in Omega-Regular Games
Iterated admissibility is a well-known and important concept in classical
game theory, e.g. to determine rational behaviors in multi-player matrix games.
As recently shown by Berwanger, this concept can be soundly extended to
infinite games played on graphs with omega-regular objectives. In this paper,
we study the algorithmic properties of this concept for such games. We settle
the exact complexity of natural decision problems on the set of strategies that
survive iterated elimination of dominated strategies. As a byproduct of our
construction, we obtain automata which recognize all the possible outcomes of
such strategies
Strategic Sophistication of Adolescents: Evidence from Experimental Normal-Form Games
We examine the strategic sophistication of adolescents, aged 10 to 17 years, in experimental normal-form games. Besides making choices, subjects have to state their first- and second-order beliefs. We find that choices are more often a best reply to beliefs if any player has a dominant strategy and equilibrium payoffs are not too unequal. Using a mixture model we can estimate for each subject the probability to be any of eight different strategic and non-strategic types. The econometric estimation reveals that older subjects are more likely to eliminate dominated strategies, and that subjects with good math grades are more strategic.strategic thinking, beliefs, experiment, age, adolescents
A cognitive hierarchy theory of one-shot games: Some preliminary results
Strategic thinking, best-response, and mutual consistency (equilibrium) are three
key modelling principles in noncooperative game theory. This paper relaxes mutual
consistency to predict how players are likely to behave in in one-shot games before they
can learn to equilibrate. We introduce a one-parameter cognitive hierarchy (CH) model
to predict behavior in one-shot games, and initial conditions in repeated games. The CH
approach assumes that players use k steps of reasoning with frequency f (k). Zero-step
players randomize. Players using k (≥ 1) steps best respond given partially rational
expectations about what players doing 0 through k - 1 steps actually choose. A simple
axiom which expresses the intuition that steps of thinking are increasingly constrained by
working memory, implies that f (k) has a Poisson distribution (characterized by a mean
number of thinking steps τ ). The CH model converges to dominance-solvable equilibria
when τ is large, predicts monotonic entry in binary entry games for τ < 1:25, and predicts
effects of group size which are not predicted by Nash equilibrium. Best-fitting values of
τ have an interquartile range of (.98,2.40) and a median of 1.65 across 80 experimental
samples of matrix games, entry games, mixed-equilibrium games, and dominance-solvable
p-beauty contests. The CH model also has economic value because subjects would have
raised their earnings substantially if they had best-responded to model forecasts instead
of making the choices they did
Experience-weighted Attraction Learning in Normal Form Games
In ‘experience-weighted attraction’ (EWA) learning, strategies have attractions that reflect initial predispositions, are updated based on payoff experience, and determine choice probabilities according to some rule (e.g., logit). A key feature is a parameter δ that weights the strength of hypothetical reinforcement of strategies that were not chosen according to the payoff they would have yielded, relative to reinforcement of chosen strategies according to received payoffs. The other key features are two discount rates, φ and ρ, which separately discount previous attractions, and an experience weight. EWA includes reinforcement learning and weighted fictitious play (belief learning) as special cases, and hybridizes their key elements. When δ= 0 and ρ= 0, cumulative choice reinforcement results. When δ= 1 and ρ=φ, levels of reinforcement of strategies are exactly the same as expected payoffs given weighted fictitious play beliefs. Using three sets of experimental data, parameter estimates of the model were calibrated on part of the data and used to predict a holdout sample. Estimates of δ are generally around .50, φ around .8 − 1, and ρ varies from 0 to φ. Reinforcement and belief-learning special cases are generally rejected in favor of EWA, though belief models do better in some constant-sum games. EWA is able to combine the best features of previous approaches, allowing attractions to begin and grow flexibly as choice reinforcement does, but reinforcing unchosen strategies substantially as belief-based models implicitly do
Thinking about Attention in Games: Backward and Forward Induction
Behavioral economics improves economic analysis by using psychological
regularity to suggest limits on rationality and self-interest (e.g. Camerer and
Loewenstein 2003). Expressing these regularities in formal terms permits productive
theorizing, suggests new experiments, can contribute to psychology,
and can be used to shape economic policies which make normal people
better off
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