Empirical Evidence on Repeated Sequential Games
نویسندگان
چکیده
منابع مشابه
Learning against sequential opponents in repeated stochastic games
This article considers multiagent algorithms that aim to find the best response in strategic interactions by learning about the game and their opponents from observations. In contrast to many state-of-the-art algorithms that assume repeated interaction with a fixed set of opponents (or even self-play), a learner in the real world is more likely to encounter the same strategic situation with cha...
متن کاملRepeated Games
I Basic Results on Normal Form Games 3 I.1 The Minmax Theorem 4 I.1.a Definitions and Notations 4 I.1.b A Basic Theorem 5 I.1.c Convexity 6 I.1.d Mixed Strategies 6 I.1.e Note on the Separation Theorem 9 Exercises 10 I.2 Complements to the Minmax Theorem 15 I.2.a The Topology on S 16 I.2.b Lack of Continuity: Regularization 16 I.2.c Lack of Compactness: Approximation 19 I.2.d Measurability: Sym...
متن کاملRepeated games
This entry shows why self-interested agents manage to cooperate in a long-term relationship. When agents interact only once, they often have an incentive to deviate from cooperation. In a repeated interaction, however, any mutually beneficial outcome can be sustained in an equilibrium. This fact, known as the folk theorem, is explained under various information structures. This entry also compa...
متن کاملRepeated Games
for every path a. The corresponding one-shot or stage game is denoted by G = ( {Ai}i=1, { fi}i=1 ) . The usual interpretation is that Ai is a set of pure actions.1 The set of feasible payoff vectors of the stage game G is given by the set F ≡ {p ∈ Rn| f (a) = p for some a ∈ A}. Let F∗ be the convex hull of the set of feasible payoffs. It should be clear that any normalized payoff in the repeate...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: SSRN Electronic Journal
سال: 2019
ISSN: 1556-5068
DOI: 10.2139/ssrn.3384725