18,237 research outputs found
Correlated Equilibria in Continuous Games: Characterization and Computation
We present several new characterizations of correlated equilibria in games
with continuous utility functions. These have the advantage of being more
computationally and analytically tractable than the standard definition in
terms of departure functions. We use these characterizations to construct
effective algorithms for approximating a single correlated equilibrium or the
entire set of correlated equilibria of a game with polynomial utility
functions.Comment: Games and Economic Behavior, In Press, Accepted Manuscript, Available
online 16 April 201
Ambiguity and social interaction
Working paper published in SSRN Electronic journal. Final version published in Oxford Economic Papers © Oxford University Press 2008. Available online at http://oep.oupjournals.org/We present a non-technical account of ambiguity in strategic games and show how it may be applied to economics and social sciences. Optimistic and pessimistic responses to ambiguity are formally modelled. We show that pessimism has the effect of increasing (decreasing) equilibrium prices under Cournot (Bertrand) competition. In addition the effects of ambiguity on peace-making are examined. It is shown that ambiguity may select equilibria in coordination games with multiple equilibria. Some comparative statics results are derived for the impact of ambiguity in games with strategic complements
A Unified View of Large-scale Zero-sum Equilibrium Computation
The task of computing approximate Nash equilibria in large zero-sum
extensive-form games has received a tremendous amount of attention due mainly
to the Annual Computer Poker Competition. Immediately after its inception, two
competing and seemingly different approaches emerged---one an application of
no-regret online learning, the other a sophisticated gradient method applied to
a convex-concave saddle-point formulation. Since then, both approaches have
grown in relative isolation with advancements on one side not effecting the
other. In this paper, we rectify this by dissecting and, in a sense, unify the
two views.Comment: AAAI Workshop on Computer Poker and Imperfect Informatio
Bandit Online Learning of Nash Equilibria in Monotone Games
We address online bandit learning of Nash equilibria in multi-agent convex
games. We propose an algorithm whereby each agent uses only obtained values of
her cost function at each joint played action, lacking any information of the
functional form of her cost or other agents' costs or strategies. In contrast
to past work where convergent algorithms required strong monotonicity, we prove
that the algorithm converges to a Nash equilibrium under mere monotonicity
assumption. The proposed algorithm extends the applicability of bandit learning
in several games including zero-sum convex games with possibly unbounded action
spaces, mixed extension of finite-action zero-sum games, as well as convex
games with linear coupling constraints.Comment: arXiv admin note: text overlap with arXiv:1904.0188
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