We consider a principal who repeatedly interacts with a strategic agent holding private information. In each round, the agent observes an idiosyncratic shock drawn independently and identically from a distribution known to the agent but not to the principal. The utilities of the principal and the agent are determined by the values of the shock and outcomes that are chosen by the principal based on reports made by the agent. When the principal commits to a dynamic mechanism, the agent best-responds to maximize his aggregate utility over the whole time horizon. The principal’s goal is to design a dynamic mechanism to minimize his worst-case regret, that is, the largest difference possible between the aggregate utility he could obtain if he knew the agent’s distribution and the actual aggregate utility he obtains. We identify a broad class of games in which the principal’s optimal mechanism is static without any meaningful dynamics. The optimal dynamic mechanism, if it exists, simply repeats an optimal mechanism for a single-round problem in each round. The minimax regret is the number of rounds times the minimax regret in the single-round problem. The class of games includes repeated selling of identical copies of a single good or multiple goods, repeated principal-agent relationships with hidden information, and repeated allocation of a resource without money. Outside this class of games, we construct examples in which a dynamic mechanism provably outperforms any static mechanism.
AbstractWe critically assess the representative consumer with quadratic aggregate utility function which forms the foundation of a well-known class of linear oligopoly demand structures. It is argued that this approach is problematic and redundant. Regarding the latter, we show how the same demand system can be derived directly from a population of heterogeneous buyers for any number of products. Welfare analyses based on aggregate demand is shown to be sensitive to the underlying microfoundation.
Interpersonal comparisons of utility can be conventional. Alternative conventions are possible. The (conventional) aggregate utility can be used for equilibrium selection. This solves the old Utilitarian problem of conflict between maximizing individual and group utility. Conditions on an equilibration dynamics leading to such a convention are given.
Utilitarianism began as a movement for social reform that changed the world. To understand Utilitarianism, we must understand utility – how is it to be measured, and how aggregate utility of a group can be understood. The authors, a cognitive scientist and a philosopher, pursue these questions from Bentham to the present, examining psychophysics, positivism, measurement theory, meaningfulness, neuropsychology, representation theorems, and dynamics of formation of conventions.
: To enhance the reliability of the link and guarantee deterministic channel access, IEEE 802.15 TG4e has introduced DSME as an amendment to IEEE 802.15.4. In this article, we analyze the throughput and energy consumption of DSME mechanism. Further, we propose optimization framework to find contention window (CW) that can enhance the aggregate utility and minimize the energy consumption of a device. Results prove that the performance of DSME is improved by 80% using the optimal setting of CW. The results are finally validated using ns-3.
This chapter summarizes the conclusions of the first part of the book and introduces the work of the second part. The first part proposed the Aggregate Utility Solution to the problem of choosing for changing selves; it argued for a particular version of this solution that aggregates particular utilities using weighted averages; and it defended that version against the objection that the utilities of different selves are incomparable and the objection that we do not know enough about our future utilities to make our decisions in these ways. This second part asks how to set the weights to which this version of the Aggregate Utility Solution appeals.
This final chapter of the book summarizes the conclusions of the preceding chapters and looks forward to how the Aggregate Utility Solution might be generalized so that it applies not only to the expected utility theory framework, but also to other frameworks for rational decision-making. In particular, it explains how we might extend the Aggregate Utility Solution to the framework of imprecise credences and utilities, and to the framework of risk-sensitive decision theories.
This chapter considers a form of practical reasoning explored by Elizabeth Harman (2009, ‘I’ll be glad I did it’ reasoning and the significance of future desires, in Philosophical Perspectives, 23(1)), which she dubs ‘I’ll be glad I did it’ reasoning, and which she rejects in general. In such reasoning, when faced with a choice between two options, if I would later think that one option is better than the other were I to choose that option, that gives me reason to choose that option. This chapter distinguishes between a number of varieties of such reasoning and applies the Aggregate Utility Solution to diagnose the problem with it. The resulting diagnosis turns out to be quite different from Harman’s.
This chapter considers two related arguments that, if successful, tell against the Aggregate Utility Solution to the problem of choosing for changing selves. The first is due to L. A. Paul (2014), ‘Voluntary Benefits from Wrongdoing’, Journal of Applied Philosophy, 31(4); the second is due to Sarah Moss (2018), Probabilistic Knowledge. Both claim that we cannot know enough to make decisions in the way proposed by the Aggregate Utility Solution. Paul appeals to considerations of authenticity; Moss appeals to knowledge norms for decision-making. The chapter responds to those arguments.
On the Microfoundation of Linear Oligopoly Demand
