Computer Science > Computer Science and Game Theory
[Submitted on 27 Jul 2017]
Title:Rationalizability and Epistemic Priority Orderings
View PDFAbstract:At the beginning of a dynamic game, players may have exogenous theories about how the opponents are going to play. Suppose that these theories are commonly known. Then, players will refine their first-order beliefs, and challenge their own theories, through strategic reasoning. I develop and characterize epistemically a new solution concept, Selective Rationalizability, which accomplishes this task under the following assumption: when the observed behavior is not compatible with the beliefs in players' rationality and theories of all orders, players keep the orders of belief in rationality that are per se compatible with the observed behavior, and drop the incompatible beliefs in the theories. Thus, Selective Rationalizability captures Common Strong Belief in Rationality (Battigalli and Siniscalchi, 2002) and refines Extensive-Form Rationalizability (Pearce, 1984; BS, 2002), whereas Strong-$\Delta$-Rationalizability (Battigalli, 2003; Battigalli and Siniscalchi, 2003) captures the opposite epistemic priority choice. Selective Rationalizability can be extended to encompass richer epistemic priority orderings among different theories of opponents' behavior. This allows to establish a surprising connection with strategic stability (Kohlberg and Mertens, 1986).
Submission history
From: EPTCS [view email] [via EPTCS proxy][v1] Thu, 27 Jul 2017 07:46:53 UTC (23 KB)
References & Citations
Bibliographic and Citation Tools
Bibliographic Explorer (What is the Explorer?)
Connected Papers (What is Connected Papers?)
Litmaps (What is Litmaps?)
scite Smart Citations (What are Smart Citations?)
Code, Data and Media Associated with this Article
alphaXiv (What is alphaXiv?)
CatalyzeX Code Finder for Papers (What is CatalyzeX?)
DagsHub (What is DagsHub?)
Gotit.pub (What is GotitPub?)
Hugging Face (What is Huggingface?)
Papers with Code (What is Papers with Code?)
ScienceCast (What is ScienceCast?)
Demos
Recommenders and Search Tools
Influence Flower (What are Influence Flowers?)
CORE Recommender (What is CORE?)
arXivLabs: experimental projects with community collaborators
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.
Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.
Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.