Learning matters: reappraising object allocation rules when agents strategically investigate

Individuals form preferences through search, interviews, discussion, and investigation. In a stylized object allocation model, we characterize the equilibrium learning strategies induced by different allocation rules and trace their welfare consequences. Our analysis reveals that top trading cycles rules dominate serial priority rules under inequality‐averse measures of social welfare

A programming-language extension for distributed real-time systems

In this paper we propose a method for extending programming languages that enables the specification of timing properties of systems. The way time is treated is not language specific and the extension can therefore be included in many existing programming languages. The presented method includes a view on the system development process. An essential feature is that it enables the construction of (hard) real-time programs that may be proven correct independently of the properties of the machines that are used for their execution. It therefore provides a similar abstraction from the execution platform as is normal for non-real-time languages. The aim of this paper is to illustrate the method and demonstrate its applicability to actual real-time problems. To this end we define a simple programming language that includes the timing extension. We present a formal semantics for a characteristic part of the language constructs and apply formal methods to prove the correctness of a small example program. We consider in detail a larger example, namely the mine-pump problem known from the literature. We construct a real-time program for this problem and describe various ways to map the program to an implementation for different platforms