From the 1 of 6 linked papers with an AI index.
6 papers
Racing to Ruin
Drew Fudenberg, Andrew Koh
The paper examines how firms competing in R&D face the risk that advancing technology could trigger a disaster that ends all payoffs, and characterizes equilibrium outcomes under p…
Persuasion and Optimal Stopping
Andrew Koh, Sivakorn Sanguanmoo, Weijie Zhong
We develop a duality-based first-order approach to dynamic persuasion in optimal stopping problems with general action-, state-, and time-dependent preferences. A direct-communicat…
Technology Speed Limits
Andrew Koh, Sivakorn Sanguanmoo
We study optimal technology regulation when private learning occurs both through doing (scaling up the technology) and through waiting (as time passes). We show that an adaptive sp…
Robust Technology Regulation
Andrew Koh, Sivakorn Sanguanmoo
We analyze how uncertain technologies should be robustly regulated and how regulation should evolve with new information. An adaptive sandbox comprising a zero marginal tax up to a…
Inertial Coordination Games
Andrew Koh, Ricky Li, Kei Uzui
We analyze inertial coordination games: dynamic coordination games with an endogenously changing state that depends on (i) a persistent fundamental players privately learn about ov…
Informational Puts
Andrew Koh, Sivakorn Sanguanmoo, Kei Uzui
We analyze how dynamic information should be provided to uniquely implement the largest equilibrium in binary-action coordination games. The designer offers an informational put: s…