Network formation by reinforcement learning
The long and medium run
Bibliographic Data
| ID | 11285292 |
|---|---|
| Authors | Robin Pemantle (The Ohio State University), Brian Skyrms (0000-0002-6961-9974, University of California, Irvine, corresponding author) |
| Year | 2004 |
| Volume | 48 |
| Issue | 3 |
| Pages | 315-327 |
| Publication date | 2004-11-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Mathematical Social Sciences (JOURNAL) |
| Journal identifiers | ISSN: 0165-4896 • E-ISSN: 1879-3118 |
| Publisher | Elsevier BV (PUBLISHER) |
| DOI | 10.1016/j.mathsocsci.2004.03.007 |
| OpenAlex | W2112233006 |
| Language | EN |
| Citations received | 7 |
| References cited | 21 |
Discounting · Econometrics · Economics · Limit (mathematics · Limiting · Mathematical analysis · Mathematical economics · Reinforcement · Reinforcement learning · Statistics · Value (mathematics · Behavioral and Psychological Studies · Complex Network Analysis Techniques · Computer Science · Engineering · Game Theory and Applications · Mathematics · Psychology · Social Psychology · Artificial Intelligence
Stochastic models for learning.
Evolution and the Theory of Games
Learning in extensive-form games
Decision field theory
On the Law of Effect 1
Experience-weighted Attraction Learning in Normal Form Games
Toward a statistical theory of learning.
Markov Learning Models for Multiperson Interactions
Learning Theory and the Logic of Critical Mass
Learning to Cooperate
| Citations per year | 0.3 |
|---|---|
| Citation span | 2003 - 2023 (21) |
| Highly cited | No |