Learning with bounded memory in stochastic models

By Seppo Honkapohja, K. Mitra. 2003

52 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Economics and Econometrics, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/47d02d0dde5373866e95184d133c3350aefcd82a

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

1. Xue-zhong He
2. Carl Chiarella
3. Stefan Nagel
4. Ulrike Malmendier
5. Youwei Li
6. Roberto Dieci
7. Cars H. Hommes
8. Laura Gardini

In Statistics and Probability

1. Carl Chiarella
2. Xue-zhong He
3. Stefan Nagel

Citations in the corpus

• HETEROGENEOUS BELIEFS, RISK, AND LEARNING IN A SIMPLE ASSET-PRICING MODEL WITH A MARKET MAKER (2003, background): “In some learning analysis, such as that of Grandmont (1985), Balasko and Royer (1996) and Honkapohja and Mitra (2000), memory is bounded because the agents forget data that has occurred far enough in the past.”
• Learning from Inflation Experiences (2016, background): “nomic outcomes and asset prices is well understood at least since Keynes (1936), we know less well how economic agents form their subjective beliefs about the future.”