765 research outputs found
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An Optimization-Based Framework for Combinatorial Prediction Market Design
We build on ideas from convex optimization to create a general framework for the design of efficient prediction markets over very large outcome spaces.Engineering and Applied Science
An Investigation Report on Auction Mechanism Design
Auctions are markets with strict regulations governing the information
available to traders in the market and the possible actions they can take.
Since well designed auctions achieve desirable economic outcomes, they have
been widely used in solving real-world optimization problems, and in
structuring stock or futures exchanges. Auctions also provide a very valuable
testing-ground for economic theory, and they play an important role in
computer-based control systems.
Auction mechanism design aims to manipulate the rules of an auction in order
to achieve specific goals. Economists traditionally use mathematical methods,
mainly game theory, to analyze auctions and design new auction forms. However,
due to the high complexity of auctions, the mathematical models are typically
simplified to obtain results, and this makes it difficult to apply results
derived from such models to market environments in the real world. As a result,
researchers are turning to empirical approaches.
This report aims to survey the theoretical and empirical approaches to
designing auction mechanisms and trading strategies with more weights on
empirical ones, and build the foundation for further research in the field
Market Design, Human Behavior, and Management
We review past research and discuss future directions on how the vibrant research areas of market design and behavioral economics have influenced and will continue to impact the science and practice of management in both the private and public sectors. Using examples from various auction markets, reputation and feedback systems in online markets, matching markets in education, and labor markets, we demonstrate that combining market design theory, behavioral insights, and experimental methods can lead to fruitful implementation of superior market designs in practice
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Computational Challenges in E-Commerce
Economic and social sciences will drive Internet protocols and services into the future.Engineering and Applied Science
A Grey-Box Approach to Automated Mechanism Design
Auctions play an important role in electronic commerce, and have been used to
solve problems in distributed computing. Automated approaches to designing
effective auction mechanisms are helpful in reducing the burden of traditional
game theoretic, analytic approaches and in searching through the large space of
possible auction mechanisms. This paper presents an approach to automated
mechanism design (AMD) in the domain of double auctions. We describe a novel
parametrized space of double auctions, and then introduce an evolutionary
search method that searches this space of parameters. The approach evaluates
auction mechanisms using the framework of the TAC Market Design Game and
relates the performance of the markets in that game to their constituent parts
using reinforcement learning. Experiments show that the strongest mechanisms we
found using this approach not only win the Market Design Game against known,
strong opponents, but also exhibit desirable economic properties when they run
in isolation.Comment: 18 pages, 2 figures, 2 tables, and 1 algorithm. Extended abstract to
appear in the proceedings of AAMAS'201
Preparing a Negotiated R&D Portfolio with a Prediction Market
The main objective of this research is to use prediction markets as negotiation agents, for supporting R&D portfolio management. To support this research, we iteratively designed, developed, operated and evaluated several prototypes. We start by presenting the weaknesses of the current techniques for managing R&D portfolio. Then, we intend to demonstrate that prediction markets correct these weaknesses in R&D portfolio management. Furthermore, following a design science paradigm, we illustrate the design of our artifacts using build-and- evaluate loops supported with a field study, which consisted in operating the prediction markets in different settings
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