English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

In this paper, zero-sum mean-field type games (ZSMFTG) with linear dynamicsand quadratic utility are studied under infinite-horizon discounted utilityfunction. ZSMFTG are a class of games in which two decision makers whoseutilities sum to zero, compete to influence a large population of agents. Inparticular, the case in which the transition and utility functions depend onthe state, the action of the controllers, and the mean of the state and theactions, is investigated. The game is analyzed and explicit expressions for theNash equilibrium strategies are derived. Moreover, two policy optimizationmethods that rely on policy gradient are proposed for both model-based andsample-based frameworks. In the first case, the gradients are computed exactlyusing the model whereas they are estimated using Monte-Carlo simulations in thesecond case. Numerical experiments show the convergence of the two players'controls as well as the utility function when the two algorithms are used indifferent scenarios.

Policy Optimization for Linear-Quadratic Zero-Sum Mean-Field Type Games