Breakdowns

TL;DR: In this article, a continuous-time, multi-armed bandit model is proposed to assess drug effectiveness by aggregating information from several channels: by continuously monitoring the state of the patient, but also by observing the occurrence of particular infrequent health events, such as relapses or disease flare-ups.

TL;DR: In this article, the authors consider a game of strategic experimentation in which players face identical discrete-time bandit problems with a safe and a risky arm, and show that the socially optimal symmetric experimentation profile can be supported as a sequential equilibrium for sufficiently optimistic prior beliefs, even if players can only communicate via binary cheap-talk messages.

TL;DR: In this paper, the design of a recommender system for organizing social learning on a product is studied and the optimal design trades off fully transparent social learning by over-recommending a product (or spamming) to a fraction of agents in the early phase of the product cycle.

TL;DR: The Curse of a Favorable Opportunity: Strategic Choice of Investment Size and Timing with Bayesian Learning.

TL;DR: In this paper, an introduction to optimal stochastic control for continuous time Markov processes and to the theory of viscosity solutions is given, as well as a concise introduction to two-controller, zero-sum differential games.

TL;DR: Controlled markov processes and viscosity solutions by W. H. Fleming and H. M. Soner as discussed by the authors, 428 pp., $ 49.95, ISBN 0-387-97927-1

TL;DR: Optimal stopping in stochastic processes: A brief review of optimal stopping and free-boundary problems can be found in this paper, along with methods of solution for solving them.

TL;DR: In this paper, the authors consider the provision of venture capital in a dynamic agency model, where the value of the venture project is initially uncertain and more information arrives by developing the project.