Shortest path problems of uncertain random networks under incomplete information environments: Models and algorithms

We study a mechanism design problem under the assumption that renegotiation cannot be prevented. We investigate what kind of equilibria of which mechanisms are renegotiation-proof under a variety of renegotiation procedures, and which social choice functions can be implemented in a way that is renegotiation-proof. In complete information environments, we show that the set of ex post renegotiation-proof implementable social choice functions contains all ex post efficient allocations when there at least three agents, but only budget balanced Groves allocations when there are two agents. In incomplete information environments with correlated beliefs and at least three agents, every ex post efficient social choice function can be implemented in the presence of ex post renegotiation, but with independent private values only social choice functions that are given by budget balanced “Groves in expectations” mechanisms are implementable in such a way. We further show that the requirement of interim renegotiation-proofness does not impose additional restrictions on implementable social choice functions under complete information, but is likely to impose additional restrictions under incomplete information.

An integrated module-based reasoning and axiomatic design approach for new product design under incomplete information environment

Exploitation vs. exploration: choosing a supplier in an environment of incomplete information

The aim of this paper is to show that strategic interaction provides a fruitful way to understand China’s decision-making behavior. States are actors in global politics and frequently have to make choices that are strategic. Credibility and uncertainty are central issues in this environment of incomplete information. This raises the question how China signals its motivations along this strategic chessboard. Strategic interaction assumes purposeful behavior from China in the African security environment. Signaling allows China to consider the problem of unknown motivations, making choices based in part, on what other actors are likely to do in the future. Knowing the choices of other African actors can help China judge what likely responses are.

Chapter 9 - Nanotechnology Risk Management: An Insurance Industry Perspective

This paper presents a systematic method for estimating the saturation point of interactive computer systems in an environment of incomplete information (in particular, where per interaction information is unavailable). This method is an improvement over the ad hoc, highly subjective, and time-consuming iterative approach commonly used. Following an operational analysis approach and using only commonly available data, a simple model was constructed to estimate the mean response time of a task characterized by its ci’u and I/O requests running in a given level of system load. The system work load is characterized by the CPU, disk, drum, and channel load factors. The system is periodically measured (or the system log examined) to obtain the parameter values needed to estimate the mean response time ofthe task as well as the corresponding work load level. With sufficient samples, a mean response time vs. system load curve can be plotted. The system saturation load is taken to be that corresponding to ...

Matching with Incomplete Information

A coordinated buyer-seller inventory model for fuzzy deteriorating items is developed under uncertain cost and demand information. The model is developed using quantity discount policy under incomplete information environment. It is observed that the solution is very close to that when one has complete information. Fuzzy set theory is used to handle the uncertainty in the input parameters. The model is analyzed using triangular membership function. The model is illustrated with a suitable numerical example.

Why do firms sometimes choose to undertake their R&D by financing start‐up companies, while other times they do it in their internal labs? We present a model where the choice of R&D is driven by information asymmetries on the quality of the project between the corporate venture capitalist and the idea owner. In an incomplete information environment, higher‐quality projects are more likely to be developed by start‐up firms, while low‐quality ones are exploited internally. Also, two types of risk are examined, intrinsic quality risk and external shock risk. Riskier project quality and more difficult project monitoring make a project more likely to be developed as a new venture. Finally, the model is able to show why corporate lab scientists get most of their compensation as a fixed salary, while idea owner entrepreneurs working for start‐up companies have a profit‐sharing agreement.

This paper considers the use of the alternating monopoly strategy (AMS) as a (tacit) collusion device. We show that firms may choose this strategy in particular environments, when other collusive strategies are also feasible. In particular, we stress how the presence of an observable move (entry), distinct from the competitive stage (price setting), can serve as a coordination device, reducing monitoring costs in incomplete information environments. The paper thus shows that AMS may be preferable to the classic market sharing strategy (MSS) and in some cases it is the only collusive equilibrium.

Externalities and private information are key characteristics of an epidemic like the Covid-19 pandemic. We study the welfare costs stemming from the incomplete information environment that these characteristics foster. We develop a framework that embeds a game theory approach into a macro SIR model to analyze the role of information in determining the extent of the health-economy trade-off of a pandemic. We apply the model to the Covid-19 epidemic in the US and find that the costs of keeping health information private are between USD $5.9$ trillion and USD $6.7$ trillion. We then find an optimal policy of disclosure and divulgation that, combined with testing and containment measures, can improve welfare. Since it is private information about individuals' health what produces the greatest welfare losses, finding ways to make such information known as precisely as possible, would result in significantly fewer deaths and significantly higher economic activity.

The price based energy consumption control is one of the key approaches for demand side management in smart grids. In this paper, the problem of load control is studied by proposing different pricing strategies from Distribution Company to the users including monthly, daily and hourly price tariffs. The users should decide on their consumption quantity and then time based on pricing strategy of the Distribution Company. The effect of price dynamics in demand side management is also studied. Due to the uncertainties and limited information available to the users, a learning approach is used for decision making of the users in an incomplete information environment. For this purpose, fuzzy Q-Learning method is adapted for learning the optimal policy of the cosumers. In this way, each user learns the best way of using electrical devices to maximize its utility and minimize price. In addition, different pricing mechanisms are compared via simulation results.

Aiming at the urgent needs of future unmanned Air combat and flight training, the methods for coordinated Air combat situation information assessment, aircraft trajectory prediction, and multi-aircraft coordinated Air combat decision-making under incomplete information environments are analyzed in the paper. The research can provide maneuver decision-making and tactical action assistance for Air combat, and contribute to the study of the winning mechanisms of intelligent warfare.

A Decision-Making Tool for Integrated Order Allocation Planning and Warehouse Systems in an Incomplete Information Environment

Stable Matching with Incomplete Information