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Locality and non-contextuality are intuitively appealing features of classical physics, which are contradicted by quantum mechanics. The goal of the classic no-go theorems by Bell, Kochen-Specker, et al. is to show that non-locality and contextuality are necessary features of any theory whose predictions agree with those of quantum mechanics. We use the(More)
The copyright to this Article is held by the Econometric Society. It may be downloaded, printed and reproduced only for educational or research purposes, including use in course packs. No downloading or copying may be done for any commercial purpose without the explicit permission of the Econometric Society. For such commercial purposes contact the Office(More)
The standard framework to analyze games with incomplete information models players as if they form beliefs about their opponents' beliefs about their opponents' beliefs and so on, that is, as if players have an infinite depth of reasoning. This strong assumption has nontrivial implications, as is well known. This paper therefore generalizes the type spaces(More)
Paradoxes of game-theoretic reasoning have played an important role in spurring developments in interactive epistemology, the area in game theory that studies the role of the players' beliefs, knowledge, etc. This paper describes two such paradoxes—one concerning backward-induction, the other iterated weak dominance. We start with the basic epistemic(More)
Both noncooperative and cooperative game theory have been applied to business strategy. We propose a hybrid noncooperative-cooperative game model, which we call a biform game. This is designed to formalize the notion of business strategy as making moves to try to shape the competitive environment in a favorable way. (The noncooperative component of a biform(More)
With applied work in mind, we define an equilibrium notion for dynamic games with assymmetric information which does not require a specification for players' beliefs about their opponents types. This enables us to define equilibrium conditions which, at least in principal , are testable and can be computed using a simple reinforcement learning algorithm. We(More)