Entropy-Regularized Optimal Transport in Information Design
Fuente:
arXiv
Gespeichert in:
| Hauptverfasser: | , , , , |
|---|---|
| Format: | Preprint |
| Veröffentlicht: |
2024
|
| Schlagworte: | |
| Online-Zugang: | |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| _version_ | 1866915061182758912 |
|---|---|
| author | Justiniano, Jorge Kleiner, Andreas Moldovanu, Benny Rumpf, Martin Strack, Philipp |
| author_facet | Justiniano, Jorge Kleiner, Andreas Moldovanu, Benny Rumpf, Martin Strack, Philipp |
| contents | In this paper, we explore a scenario where a sender provides an information policy and a receiver, upon observing a realization of this policy, decides whether to take a particular action, such as making a purchase. The sender's objective is to maximize her utility derived from the receiver's action, and she achieves this by careful selection of the information policy. Building on the work of Kleiner et al., our focus lies specifically on information policies that are associated with power diagram partitions of the underlying domain. To address this problem, we employ entropy-regularized optimal transport, which enables us to develop an efficient algorithm for finding the optimal solution. We present experimental numerical results that highlight the qualitative properties of the optimal configurations, providing valuable insights into their structure. Furthermore, we extend our numerical investigation to derive optimal information policies for monopolists dealing with multiple products, where the sender discloses information about product qualities. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2412_09316 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Entropy-Regularized Optimal Transport in Information Design Justiniano, Jorge Kleiner, Andreas Moldovanu, Benny Rumpf, Martin Strack, Philipp Numerical Analysis Computer Science and Game Theory Optimization and Control 49Q22, 65K10, 91B03 In this paper, we explore a scenario where a sender provides an information policy and a receiver, upon observing a realization of this policy, decides whether to take a particular action, such as making a purchase. The sender's objective is to maximize her utility derived from the receiver's action, and she achieves this by careful selection of the information policy. Building on the work of Kleiner et al., our focus lies specifically on information policies that are associated with power diagram partitions of the underlying domain. To address this problem, we employ entropy-regularized optimal transport, which enables us to develop an efficient algorithm for finding the optimal solution. We present experimental numerical results that highlight the qualitative properties of the optimal configurations, providing valuable insights into their structure. Furthermore, we extend our numerical investigation to derive optimal information policies for monopolists dealing with multiple products, where the sender discloses information about product qualities. |
| title | Entropy-Regularized Optimal Transport in Information Design |
| topic | Numerical Analysis Computer Science and Game Theory Optimization and Control 49Q22, 65K10, 91B03 |
| url | https://arxiv.org/abs/2412.09316 |