English

The Structure of Signals: Causal Interdependence Models for Games of Incomplete Information

Computer Science and Game Theory 2012-02-20 v1 Artificial Intelligence

Abstract

Traditional economic models typically treat private information, or signals, as generated from some underlying state. Recent work has explicated alternative models, where signals correspond to interpretations of available information. We show that the difference between these formulations can be sharply cast in terms of causal dependence structure, and employ graphical models to illustrate the distinguishing characteristics. The graphical representation supports inferences about signal patterns in the interpreted framework, and suggests how results based on the generated model can be extended to more general situations. Specific insights about bidding games in classical auction mechanisms derive from qualitative graphical models.

Keywords

Cite

@article{arxiv.1202.3768,
  title  = {The Structure of Signals: Causal Interdependence Models for Games of Incomplete Information},
  author = {Michael P. Wellman and Lu Hong and Scott E. Page},
  journal= {arXiv preprint arXiv:1202.3768},
  year   = {2012}
}