Collaborative Research: Sophisticated Learning and Strategic Teaching in Repeated Games

University Of California-Berkeley, Berkeley CA

Investigators

Abstract

Ho #0078853 Our research addresses how people and organizations learn from experience in strategic situations like bargaining, coordinating joint actions (teamwork), choosing prices and features for new products, bidding in auctions, etc. In previous research we discovered a mathematical formula which explains how people appear to learn from experience, but the numerical details of the formula (its "parameters) seem to vary from situation to situation, as if people are learning in different ways. We therefore propose to explore why these parameters seem to vary. In addition, most mathematical theories of strategic learning assume that people only look back at past experiences. We also propose to extend these theories to allow for people who realize that other people are learning from experience, and are able to therefore outguess what others will do based on what happened in the past. If players are "sophisticated", in this sense, it pays for them to take actions that are not perfect in the near-term, to "teach" other players who are learning to take actions which will benefit the "teachers" in the long-term. This teaching can be beneficial for the teacher but bad for society (e.g., when firms scare away innovative competitors by threatening illegal retaliation), or beneficial for everyone (e.g., when firms reassure others that they can be trusted). Our research develops a precise mathematical theory of how sophisticated players behave and when it pays for them to teach. We use the theory to explain observations from experiments and predicts whether teaching will occur in new situations.